Anti-inflammatory effects and related mechanisms in vitro and in vivo of Hedychium coccineum rhizome essential oil

ETHNOPHARMACOLOGICAL RELEVANCE

Hedychium coccineum rhizome is an anti-inflammatory ethnomedicine used to remedy inflammation-related swelling and bronchial asthma.

AIM OF THE STUDY

The study aimed to analyze the phytochemical constituents of H. coccineum rhizome essential oil (EO) and evaluate its in vitro and in vivo anti-inflammatory effects and underlying mechanisms.

MATERIALS AND METHODS

Phytochemical constituents of H. coccineum rhizome EO were analyzed using GC-FID/MS. In RAW264.7 macrophages induced by LPS, blockade of PGE2, NO, IL-1β, IL-6, and TNF-α secretion by H. coccineum rhizome EO was measured, and then Western blot, qRT-PCR, and immunofluorescent staining were used to evaluate its underlying mechanisms. Moreover, we used the xylene-induced ear edema model for testing anti-inflammatory potential in vivo and examined auricular swelling as well as tissue and serum contents of IL-1β, IL-6, and TNF-α.

RESULTS

EO's main components were E-nerolidol (40.5%), borneol acetate (24.8%), spathulenol (4.5%), linalool (3.8%), elemol (3.5%), and borneol (3.4%). In RAW264.7 cells stimulated by LPS, EO downregulated the expression of pro-inflammatory enzyme (iNOS and COX-2) genes and proteins, thereby suppressing pro-inflammatory mediators (NO and PGE2) secretion. Simultaneously, it reduced TNF-α, IL-1β, and IL-6 release by downregulating their mRNA expression. Besides, H. coccineum EO attenuated LPS-stimulated activation of NF-κB (by reducing IκBα phosphorylation and degradation to inhibit NF-κB nuclear translocation) and MAPK (by downregulating JNK, p38, and ERK phosphorylation). In xylene-induced mouse ear edema, EO relieved auricular swelling and lowered serum and tissue levels of TNF-α, IL-1β, and IL-6.

CONCLUSIONS

H. coccineum EO had powerful in vivo and in vitro anti-inflammatory effects by inhibiting MAPK and NF-κB activation. Hence, H. coccineum EO should have great potential for application in the pharmaceutical field as a novel anti-inflammatory agent.

Integrative analysis of the cuproptosis-related gene ATP7B in the prognosis and immune infiltration of IDH1 wild-type glioma

Glioma is the most common malignant tumor in the brain and the central nervous system with a poor prognosis, and wild-type isocitrate dehydrogenase (IDH) glioma indicates a worse prognosis. Cuproptosis is a recently discovered form of cell death regulated by copper-dependent mitochondrial respiration. However, the effect of cuproptosis on tumor prognosis and immune infiltration is not clear. In this research, we analyzed of public databases to show the correlation between cuproptosis-related genes and the prognosis of IDH1 wild-type glioma. Nine out of 12 genes were upregulated in IDH1 wild-type glioma patients, and 6 genes were significantly associated with overall survival (OS), while 5 genes were associated with progression-free survival (PFS). Then, we constructed a prognostic cuproptosis-related gene signature for IDH1 wild-type glioma patients. ATP7B was considered an independent prognostic indicator, and a low expression level of ATP7B was related to a shorter period of OS and PFS. Moreover, downregulation of ATP7B was correlated not only with the infiltration of activated NK cells, CD8 + T cells and M2 macrophages; but also with high expression of immune checkpoint genes and tumor mutation burden (TMB). In the IDH1 wild-type glioma tissues we collected, our data also confirmed that high tumor grade was accompanied by low expression of ATP7B and high expression of PD-L1, which was associated with increasing infiltration of CD8 + immune cells. In conclusion, our research constructed a prognostic cuproptosis-related gene signature model to predict the prognosis of IDH1 wild-type glioma. ATP7B is deemed to be a potential prognostic indicator and novel immunotherapy biomarker for IDH1 wild-type glioma patients.

A Universal and Programmable Platform based on Fluorescent Peptide-Conjugated Probes for Detection of Proteins in Organelles of Living Cells

Realizing protein analysis in organelles of living cells is of great significance for developing diagnostic and therapeutic methods of diseases. Fluorescent-labeled antibodies with well imaging performance and high affinity are classical biochemical tools for protein analysis, while due to the inability to effectively enter into cells, not to mention organelles and the uncontrollable reaction sites that might cause antibodies inactivation when chemically modification, they are hard to apply to living cells. Inspired by the structure of fluorescent-labeled antibodies, we designed as a universal detection platform that was based on the peptide-conjugated probes (PCPs) and consisted of three parts: a) a rotor type fluorescent molecular scaffold for conjugation and signal output; b) the cell penetration protein recognition unit; c) the subcellular organelle targeting unit. In living cells, PCPs could firstly localize at organelles and then proceed protein specific recognition, thus jointly leading to the restriction of twisted intramolecular charge transfer and activation of fluorescence signal. As a proof-of-concept, six different proteins in three typical intracellular organelles could be detected by our platform through simply replacing the recognition sequence of proteins and matching organelle targeting units. The position and intensity of fluorescence signals demonstrated specificity of PCPs and universality of the platform.

The Friction-Lubrication Effect and Compaction Characteristics of an SMA Asphalt Mixture under Variable Temperature Conditions

The aim of this article is to explore the dynamic compaction characteristics of stone mastic asphalt (SMA) and the friction-lubrication effect of internal particles during the superpave gyratory compaction (SGC) process. Firstly, a calculated method for the compaction degree of an asphalt mixture in the gyratory compaction process was defined based on the multiphase granular volume method. Secondly, the gyratory compaction curves of asphalt mixtures were taken based on this calculation method of compaction degree. The dynamic change law of each compaction index (compaction, percentage of air voids, compaction energy index, etc.) during the compaction process was analysed. Finally, the effects of different initial compaction temperatures and different asphalt content on the friction-lubrication effect and compaction characteristics of asphalt mixtures were studied. Research shows that it is reasonable to define the compaction degree by the ratio of the apparent density of the asphalt mixture to the maximum theoretical density of the asphalt mixture during gyratory compaction. The dynamic prediction equations of the compaction degree K and the compaction energy index CEI with the amount of compaction were established, and could effectively predict the compaction degree, percentage of air voids and compaction energy index CEI. The compaction process of the asphalt mixture needed to go through three phases, including periods of rapid growth, slow growth, and stabilisation, and the compaction degree increased by about 10%, 5%, and 1%, in that order, finally tending towards a stable value. The effect of the initial compaction temperature on the forming compaction degree of the asphalt mixture is significant; therefore, it should be controlled strictly in the compaction construction of asphalt mixtures. When the initial compaction temperature of SMA-13 is about 170 °C, the compaction effect is optimal, and the effect of the increase in the amount of compaction at a later stage on the increase in the compaction degree of the asphalt mixture is very low. With the optimal asphalt content, the friction-lubrication effect between the asphalt and aggregate particles is optimal, because it can effectively form an asphalt film, reducing the frictional resistance of the particles moving each other during the compaction process, and the voids will be embedded and filled with each other, finally producing the best compaction result.

Robust miniature Cas-based transcriptional modulation by engineering Un1Cas12f1 and tethering Sso7d

The miniature V-F CRISPR-Cas12f system has been repurposed for gene editing and transcription modulation. The small size of Cas12f satisfies the packaging capacity of adeno-associated virus (AAV) for gene therapy. However, the efficiency of Cas12f-mediated transcriptional activation varies among different target sites. Here, we developed a robust miniature Cas-based transcriptional activation or silencing system using Un1Cas12f1. We engineered Un1Cas12f1 and the cognate guide RNA and generated miniCRa, which led to a 1,319-fold increase in the activation of the ASCL1 gene. The activity can be further increased by tethering DNA-binding protein Sso7d to miniCRa and generating SminiCRa, which reached a 5,628-fold activation of the ASCL1 gene and at least hundreds-fold activation at other genes examined. We adopted these mutations of Un1Cas12f1 for transcriptional repression and generated miniCRi or SminiCRi, which led to the repression of ∼80% on average of eight genes. We generated an all-in-one AAV vector AIOminiCRi used to silence the disease-related gene SERPINA1. AIOminiCRi AAVs led to the 70% repression of the SERPINA1 gene in the Huh-7 cells. In summary, miniCRa, SminiCRa, miniCRi, and SminiCRi are robust miniature transcriptional modulators with high specificity that expand the toolbox for biomedical research and therapeutic applications.

Gut microbiota-derived 5-hydroxyindoleacetic acid from pumpkin polysaccharides supplementation alleviates colitis via MAPKs-PPARγ/NF-κB inhibition

Polysaccharides from Pumpkin (Cucurbita moschata Duchesne) (PPs) have many pharmacological activities, including anti-oxidant, immune, and intestinal microbiota regulation. These activities have provided some reminders of its potential therapeutic effect on ulcerative colitis (UC), but this has not yet been confirmed. This study preliminarily confirmed its significant anti-UC activity superior to Salicylazosulfapyridine. The average molecular weight of PPs was 3.10 × 105 Da, and PPs mainly comprised Mannose, Rhamnose, Galacturonic acid, Galactosamine, Glucose, and Xylose with molar ratios of 1.58:3.51:34.54:1.00:3.25:3.02. PPs (50, 100 mg/kg) could significantly resist dextran sodium sulfate induced UC on C57BL/6 mice by improving gut microbiota dysbiosis, such as the changes of relative abundance of Bacteroides, Culturomica, Mucispirillum, Escherichia-Shigella, Alistipes and Helicobacter. PPs also reverse the abnormal inflammatory reaction, including abnormal level changes of TNF-α, IFN-γ, IL-1β, IL-4, IL-6, IL-10, and IL-18. Metabolomic profiling showed that PPs supplementation resulted in the participation of PPAR and MAPK pathways, as well as the increase of 5-hydroxyindole acetic acid (5-HIAA) level. 5-HIAA also exhibited individual and synergistic anti-UC activities in vivo. Furthermore, combination of PPs and 5-HIAA could also elevate the levels of PPARγ in nuclear and inhibit MAPK/NF-ĸB pathway in the colon. This study revealed that PPs and endogenous metabolite 5-HIAA might be developed to treat UC.

Effect of endoscopic mucosal resection and endoscopic submucosal dissection on postoperative wound complications in patients with gastric cancer: A meta-analysis

Endoscopic submucosa dissection (ESD) allows complete excision of the whole lesion, which results in a higher percentage of complete excision and an improved quality of life by minimizing the amount of excision as opposed to an endoscopic mucosal resection (EMR). Although ESD is now being carried out in the majority of hospitals, ESD's possible complications (such as trauma and perforation) have given rise to doubts about ESD practices in patients with early-stage stomach cancer when deciding on therapy and reimbursement. This study was designed to evaluate the effectiveness and safety of ESD over EMR in treating early-stage stomach cancer. Four main databases have been searched, including EMBASE and published. The ROBINS-I tool suggested in the Cochrane Handbook has been applied to evaluate the quality of the chosen trials. It may better reflect the risk of bias in the included studies. The meta-analyses were carried out with ReMan 5.3, and the results were treated with endote. Seven cohort studies have been completed. Meta analysis indicated that EMR and ESD surgery did not differ significantly from each other in terms of postoperative haemorrhage (OR, 0.76; 95%CI, 0.56,1.04 p = 0.09); EMR, however, was associated with a lower rate of postoperative perforation than ESD surgery (OR, 0.36; 95%CI, 0.24,0.54 p < 0.0001). Taking into account that ESD and EMR did not differ significantly in the risk of wound bleeding, even though the risk of perforation is not likely to result in life-threatening illness. In the analysis of these data, however, the potential advantages of EMR might be greater than ESD.

Disturbance of mitochondrial dynamics in myocardium of broilers with pulmonary hypertension syndrome

1. The following study investigated the relationship between pulmonary hypertension syndrome (PHS) and mitochondrial dynamics in broiler cardiomyocytes.2. An animal model for PHS was established by injecting broiler chickens with CM-32 cellulose particles. Broiler myocardial cells were cultured under hypoxic conditions to establish an in vitro model. The ascites heart index, histomorphology, mitochondrial ultrastructure, and mitochondrial dynamic-related gene and protein expression were evaluated.3. The myocardial fibres from PHS broilers had wider spaces and were wavy and twisted and the number of mitochondria increased. Compared with the control group, the gene and protein expression levels were decreased for Opa1, Mfn1, and Mfn2 in the myocardium of PHS broilers. The gene and protein expression was significantly increased for Drp1 and Mff.4. This study showed that PHS in broilers may cause myocardial mitochondrial dysfunction, specifically by diminishing mitochondrial fusion and enhancing fission, causing disturbances in the mitochondrial dynamics of the heart.

Associations of different isomeric forms of serum lycopene with cardiovascular disease and all-cause mortality

Background: The effect of serum lycopene on the progression of cardiovascular diseases (CVDs) and their longevity remains a controversial topic. The purpose of this study was to evaluate the associations of different isomeric forms of serum lycopene with CVD and all-cause mortality in the American population. Methods: The National Health and Nutrition Examination Survey (NHANES) is a large population survey to investigate public health in the US. We analyzed data from 2003-2006 linked with mortality data obtained in 2015. Cox proportional hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated to assess the risk of CVD and all-cause mortality caused by serum lycopene. Results: Among 7452 participants (aged 20-85 years, 46.7% male), 298 died from CVDs among the total 1213 deaths during a median follow-up of 10.7 years. Serum lycopene is a protective factor for all-cause and CVD mortality. In multivariable-adjusted models, the hazard ratio (with 95% confidence intervals) associated with Q4 compared to Q1 of serum total-lycopene, trans-lycopene and cis-lycopene was 0.49 (0.38,0.63), 0.49 (0.39,0.63) and 0.55 (0.43,0.70) for all-cause mortality (Ptrend<0.05), and was 0.53 (0.32,0.96), 0.48 (0.32,0.72) and 0.63 (0.41,0.97) for CVD mortality (Ptrend<0.05). The subgroup analyses showed that different isomeric forms of lycopene showed varied associations with CVD and all-cause mortality based on age, drinking status, history of hypertension and diabetes. Conclusions: Serum lycopene concentration was significantly associated with the risk of CVD and all-cause mortality. Cis-lycopene had a U-shaped relationship with mortality, while trans-lycopene had an inverse relationship with it.

Traditional Chinese medicine polysaccharide in nano-drug delivery systems: Current progress and future perspectives

Traditional Chinese medicine polysaccharides (TCMPs) have gained increasing attention in the field of nanomedicine due to their diverse biological activities and favorable characteristics as drug carriers, including biocompatibility, biodegradability, safety, and ease of modification. TCMPs-based nano-drug delivery systems (NDDSs) offer several advantages, such as evasion of reticuloendothelial system (RES) phagocytosis, protection against biomolecule degradation, enhanced drug bioavailability, and potent therapeutic effects. Therefore, a comprehensive review of the latest developments in TCMPs-based NDDSs and their applications in disease therapy is of great significance. This review provides an overview of the structural characteristics and biological activities of TCMPs relevant to carrier design, the strategies employed for constructing TCMPs-based NDDSs, and the versatile role of TCMPs in these systems. Additionally, current challenges and future prospects of TCMPs in NDDSs are discussed, aiming to provide valuable insights for future research and clinical translation.

Targeted long-read sequencing for comprehensive detection of CYP21A2 mutations in patients with 21-hydroxylase deficiency

BACKGROUND

21-Hydroxylase deficiency (21-OHD) is caused by pathogenic CYP21A2 variations. CYP21A2 is arranged in tandem with its highly homologous pseudogene CYP21A1P; therefore, it is prone to mismatch and rearrangement, producing different types of complex variations. There were few reports on using only one method to detect different CYP21A2 variants simultaneously.

AIMS

Targeted long-read sequencing method was used to detect all types of CYP21A2 variants in a series of patients with 21-OHD.

METHODS

A total of 59 patients with 21-OHD were enrolled from Peking Union Medical College Hospital. Long-range locus-specific PCR and long-read sequencing (LRS) were performed to detect the pathogenic variants in CYP21A2.

RESULTS

Copy-number variants of CYP21A2 were found in 25.4% of patients, including 5.1% with 3 copies of CYP21A2, 16.9% with 1 copy of CYP21A2, and 3.4% with 0 copy of CYP21A2. The remaining 74.6% of patients had 2 copies of CYP21A2. Pathogenic variants were identified in all 121 alleles of 59 patients. Specifically, single-nucleotide variants and small insertions/deletions (< 50 bp) were detected in 79 alleles, of which conversed from CYP21A1P were detected in 63 alleles, and rare variants were found in the other 16 alleles. Large gene conversions (> 50 bp) from pseudogene were detected in 10 alleles, and different chimeric genes (CYP21A1P/CYP21A2 or TNXA/TNXB) formed by large deletions were detected in 32 alleles. Of all variants, p.I173N was the most common variant (19.0%).

CONCLUSIONS

Our study demonstrated that targeted long-read sequencing is a comprehensive method for detecting CYP21A2 variations, which is helpful for genetic diagnosis in 21-OHD patients.

Fragility index analysis for randomized controlled trials of approved biologicals and small molecule drugs in inflammatory bowel diseases

INTRODUCTION

Biologics and small molecules have been increasingly applied in Crohn's disease (CD) and ulcerative colitis (UC). But the robustness of their trials has not been evaluated.

METHODS

We initially collected all the approved biologics or small molecules for CD or UC up to December 1, 2022. Databases were then queried by keywords in chemical name and CD or UC. Randomized controlled trials (RCTs) in the two-arm, 1:1 design were included. Fragility index (FI) and fragility quotient (FQ) were subsequently calculated.

RESULTS

We included twenty-eight RCTs, including nine pivotal trials listed in approval labels, nineteen non-pivotal trials not included in the labels. The median sample size was 99 [IQR, 60-262] and the median number of loss-of-follow-up (LFU) was 14 [IQR, 8-43]. Pivotal trials in the labels had the median FI of 8 [IQR, 4-14, n = 6] that was marginally higher than non-pivotal trials (3 [IQR, 2-4], p = 0.08). The median FQ was 0.0330 [IQR, 0.1220-0.0466] and 0.0310 [IQR, 0.0129-0.0540] for pivotal and non-pivotal trials, respectively (p = 1.0). The sample size and FI were significantly correlated (Spearman correlation coefficient [r] = 0.56, 95 %CI 0.21-0.78, p = 0.003). The number of total events was also significantly correlated with FI (r = 0.53, 95 %CI 0.17-0.77, p = 0.006). Study p-values were significantly associated with FI (p = 0.01): trials with p-values < 0.001 had the highest median FI of 10 [IQR, 6-17]. No factor was found strongly correlated with FQ.

CONCLUSION

Results from trials assessing administration-approved biologics or small molecules for treating CD or UC were vulnerable to small changes by measuring FI or FQ. Pivotal studies contributing to regulatory approvals exhibited a relatively higher degree of resilience compared to non-pivotal trials.

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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Study of High-Transverse-Momentum Higgs Boson Production in Association with a Vector Boson in the qqbb Final State with the ATLAS Detector

This Letter presents the first study of Higgs boson production in association with a vector boson (V=W or Z) in the fully hadronic qqbb final state using data recorded by the ATLAS detector at the LHC in proton-proton collisions at sqrt[s]=13  TeV and corresponding to an integrated luminosity of 137  fb^{-1}. The vector bosons and Higgs bosons are each reconstructed as large-radius jets and tagged using jet substructure techniques. Dedicated tagging algorithms exploiting b-tagging properties are used to identify jets consistent with Higgs bosons decaying into bb[over ¯]. Dominant backgrounds from multijet production are determined directly from the data, and a likelihood fit to the jet mass distribution of Higgs boson candidates is used to extract the number of signal events. The VH production cross section is measured inclusively and differentially in several ranges of Higgs boson transverse momentum: 250-450, 450-650, and greater than 650 GeV. The inclusive signal yield relative to the standard model expectation is observed to be μ=1.4_{-0.9}^{+1.0} and the corresponding cross section is 3.1±1.3(stat)_{-1.4}^{+1.8}(syst)  pb.

Phytochemical analysis and anticancer effect of Camellia oleifera bud ethanol extract in non-small cell lung cancer A549 cells

Camellia oleifera is a medicine food homology plant widely cultivated in the Yangtze River Basin and southern China due to its camellia oil. Camellia oleifera bud and fruit exist simultaneously, and its bud is largely discarded as waste. However, C. oleifera bud has been used in traditional Chinese medicine to treat a variety of ailments. Thus, the purpose of this study was to identify the chemical components of C. oleifera bud ethanol extract (EE) and first evaluate its anticancer effects in non-small cell lung cancer A549 cells. Based on UHPLC-Q-Orbitrap-MS analysis, seventy components were identified. For anticancer activity, C. oleifera bud EE had remarkable cytotoxic effect on non-small cell lung cancer A549 (IC50: 57.53 ± 1.54 μg/mL) and NCI-H1299 (IC50: 131.67 ± 4.32 μg/mL) cells, while showed lower cytotoxicity on non-cancerous MRC-5 (IC50 > 320 μg/mL) and L929 (IC50: 179.84 ± 1.08 μg/mL) cells. It dramatically inhibited the proliferation of A549 cells by inducing cell cycle arrest at the G1 phase. Additionally, it induced apoptosis in A549 cells through a mitochondria-mediated pathway, which decreased mitochondrial membrane potential, upregulated Bax, activated caspase 9 and caspase 3, and resulted in PARP cleavage. Wound healing and transwell invasion assays demonstrated that C. oleifera bud EE inhibited the migration and invasion of A549 cells in a dose-dependent manner. The above findings indicated that C. oleifera bud EE revealed notable anticancer effects by inhibiting proliferation, inducing apoptosis, and suppressing migration and invasion of A549 cells. Hence, C. oleifera bud ethanol extract could serve as a new source of natural anticancer drugs.

Reproductive factors and risk of lung cancer among 300,000 Chinese female never-smokers: evidence from the China Kadoorie Biobank study

BACKGROUND

Lung cancer is the leading cause of cancer mortality among Chinese females despite the low smoking prevalence among this population. This study assessed the roles of reproductive factors in lung cancer development among Chinese female never-smokers.

METHODS

The prospective China Kadoorie Biobank (CKB) recruited over 0.5 million Chinese adults (0.3 million females) from 10 geographical areas in China in 2004-2008 when information on socio-demographic/lifestyle/environmental factors, physical measurements, medical history, and reproductive history collected through interviewer-administered questionnaires. Cox proportional hazard regression was used to estimate adjusted hazard ratios (HRs) of lung cancer by reproductive factors. Subgroup analyses by menopausal status, birth year, and geographical region were performed.

RESULTS

During a median follow-up of 11 years, 2,284 incident lung cancers occurred among 282,558 female never-smokers. Ever oral contraceptive use was associated with a higher risk of lung cancer (HR = 1.16, 95% CI: 1.02-1.33) with a significant increasing trend associated with longer duration of use (p-trend = 0.03). Longer average breastfeeding duration per child was associated with a decreased risk (0.86, 0.78-0.95) for > 12 months compared with those who breastfed for 7-12 months. No statistically significant association was detected between other reproductive factors and lung cancer risk.

CONCLUSION

Oral contraceptive use was associated with an increased risk of lung cancer in Chinese female never-smokers. Further studies are needed to assess lung cancer risk related to different types of oral contraceptives in similar populations.

Piperine promotes PI3K/AKT/mTOR-mediated gut-brain autophagy to degrade α-Synuclein in Parkinson's disease rats

ETHNOPHARMACOLOGICAL RELEVANCE

Piper longum L., a medicinal and food homologous herb, has a traditional history of use in treating gastrointestinal and neurological disorders. Piperine (PIP) the main alkaloid of P. longum, exists neuroprotective effects on various animal models of Parkinson's disease (PD). Nevertheless, the underlying mechanism, particularly the role of PIP in promoting gut-brain autophagy for α-Synuclein (α-Syn) degradation in PD, remains incompletely understood.

AIM OF THE STUDY

To explore the role of PIP in regulating the gut-brain autophagy signaling pathway to reduce α-Syn levels in both the colon and substantia nigra (SN) of PD model rats.

MATERIALS AND METHODS

Behavioral experiments were conducted to assess the impact of PIP on 6-hydroxydopamine (6-OHDA)-induced PD rats. The intestinal microbiome composition and intestinal metabolites were analyzed by metagenomics and GC-MS/MS. The auto-phagosomes were visualized by transmission electron microscopy. Immunohistochemistry, immunofluorescence, and western blotting were performed to assess the levels of tyrosine hydroxylase (TH), α-Syn, LC3II/LC3I, p62, and the PI3K/AKT/mTOR pathway in both the SN and colon of the rats. The pathway-related inhibitor and agonist were used to verify the autophagy mechanism in the SH-SY5Y cells overexpressing A53T mutant α-Syn (A53T-α-Syn).

RESULTS

PIP improved autonomic movement and gastrointestinal dysfunctions, reduced α-Syn aggregation and attenuated the loss of dopaminergic neurons in 6-OHDA-induced PD rats. After oral administration of PIP, the radio of LC3II/LC3I increased and the expression of p62 was degraded, as well as the phosphorylation levels of PI3K, AKT and mTOR decreased in the SN and colon of rats. The effect of PIP on reducing A53T-α-Syn through the activation of the PI3K/AKT/mTOR-mediated autophagy pathway was further confirmed in A53T-α-Syn transgenic SH-SY5Y cells. This effect could be inhibited by the autophagy inhibitor bafilomycin A1 and the PI3K agonist 740 Y-P.

CONCLUSIONS

Our findings suggested that PIP could protect neurons by activating autophagy to degrade α-Syn in the SN and colon, which were related to the suppression of PIP on the activation of PI3K/AKT/mTOR signaling pathway.

Switching action modes of miR408-5p mediates auxin signaling in rice

MicroRNAs (miRNAs) play fundamental roles in many developmental and physiological processes in eukaryotes. MiRNAs in plants generally regulate their targets via either mRNA cleavage or translation repression; however, which approach plays a major role and whether these two function modes can shift remains elusive. Here, we identify a miRNA, miR408-5p that regulates AUXIN/INDOLE ACETIC ACID 30 (IAA30), a critical repressor in the auxin pathway via switching action modes in rice. We find that miR408-5p usually inhibits IAA30 protein translation, but in a high auxin environment, it promotes the decay of IAA30 mRNA when it is overproduced. We further demonstrate that IDEAL PLANT ARCHITECTURE1 (IPA1), an SPL transcription factor regulated by miR156, mediates leaf inclination through association with miR408-5p precursor promoter. We finally show that the miR156-IPA1-miR408-5p-IAA30 module could be controlled by miR393, which silences auxin receptors. Together, our results define an alternative auxin transduction signaling pathway in rice that involves the switching of function modes by miR408-5p, which contributes to a better understanding of the action machinery as well as the cooperative network of miRNAs in plants.

Washed microbiota transplantation for Crohn's disease: A metagenomic, metatranscriptomic, and metabolomic-based study

BACKGROUND

Fecal microbiota transplantation (FMT) is a promising therapeutic approach for treating Crohn's disease (CD). The new method of FMT, based on the automatic washing process, was named as washed microbiota transplantation (WMT). Most existing studies have focused on observing the clinical phenomena. However, the mechanism of action of FMT for the effective management of CD-particularly in-depth multi-omics analysis involving the metagenome, metatranscriptome, and metabolome-has not yet been reported.

AIM

To assess the efficacy of WMT for CD and explore alterations in the microbiome and metabolome in response to WMT.

METHODS

We conducted a prospective, open-label, single-center clinical study. Eleven CD patients underwent WMT. Their clinical responses (defined as a decrease in their CD Activity Index score of > 100 points) and their microbiome (metagenome, metatranscriptome) and metabolome profiles were evaluated three months after the procedure.

RESULTS

Seven of the 11 patients (63.6%) showed an optimal clinical response three months post-WMT. Gut microbiome diversity significantly increased after WMT, consistent with improved clinical symptoms. Comparison of the metagenome and metatranscriptome analyses revealed consistent alterations in certain strains, such as Faecalibacterium prausnitzii, Roseburia intestinalis, and Escherichia coli. In addition, metabolomics analyses demonstrated that CD patients had elevated levels of various amino acids before treatment compared to the donors. However, levels of vital amino acids that may be associated with disease progression (e.g., L-glutamic acid, gamma-glutamyl-leucine, and prolyl-glutamine) were reduced after WMT.

CONCLUSION

WMT demonstrated therapeutic efficacy in CD treatment, likely due to the effective reconstruction of the patient's microbiome. Multi-omics techniques can effectively help decipher the potential mechanisms of WMT in treating CD.

A major facilitator superfamily transporter MdtH in Escherichia coli is involved in anthocyanin biosynthesis and secretion

Anthocyanin cyanidin 3-O-glucoside (C3G) is a natural pigment widely used in food and nutraceutical industries. Its microbial synthesis in Escherichia coli is a promising and efficient way toward large-scale production. The current production titer is low partly due to the accumulation of C3G inside the producing microbes; thus, it is important to explore native transporters responsible for anthocyanin secretion. Currently, there has been only one native E. coli transporter identified with C3G-transporting capability, and its overexpression has a very limited effect on the promotion of extracellular C3G production. In this study, we report the identification and verification of an efficient intrinsic C3G efflux transporter MdtH in E. coli through transcriptomic analysis and genetic/biochemical studies. MdtH could bind C3G with high affinity, and its overexpression increased the extracellular C3G biosynthesis in E. coli by 110%. Our study provides a new regulation target for microbial biosynthesis of C3G and other anthocyanins.

IMPORTANCE

Cyanidin 3-O-glucoside (C3G) is a natural colorant with health-promoting activities and is, hence, widely used in food, cosmetic, and nutraceutical industries. Its market supply is currently dependent on extraction from plants. As an alternative, C3G can be produced by the microbe Escherichia coli in a green and sustainable way. However, a large portion of this compound is retained inside the cell of E. coli, thus complicating the purification process and limiting the high-level production. We have identified and verified an efficient native transporter named MdtH in E. coli that can export C3G to the cultivation medium. Overexpression of MdtH could improve extracellular C3G production by 110% without modifications of the metabolic pathway genes or enzymes. This study reveals a new regulation target for C3G production in bacteria and provides guidance to the microbial biosynthesis of related compounds.

Biochar's role in improving pakchoi quality and microbial community structure in rhizosphere soil

Background

Biochar amendments enhance crop productivity and improve agricultural quality. To date, studies on the correlation between different amounts of biochar in pakchoi (Brassica campestris L.) quality and rhizosphere soil microorganisms are limited, especially in weakly alkaline soils. The experiment was set up to explore the effect of different concentrations of biochar on vegetable quality and the correlation between the index of quality and soil bacterial community structure changes.

Methods

The soil was treated in the following ways via pot culture: the blank control (CK) without biochar added and with biochar at different concentrations of 1% (T1), 3% (T2), 5% (T3), and 7% (T4). Here, we investigatedthe synergistic effect of biochar on the growth and quality of pakchoi, soil enzymatic activities, and soil nutrients. Microbial communities from pakchoi rhizosphere soil were analyzed by Illumina MiSeq.

Results

The results revealed that adding 3% biochar significantly increased plant height, root length, and dry weight of pakchoi and increased the contents of soluble sugars, soluble proteins, Vitamin C (VC), cellulose, and reduced nitrate content in pakchoi leaves. Meanwhile, soil enzyme activities and available nutrient content in rhizosphere soil increased. This study demonstrated that the the microbial community structure of bacteria in pakchoi rhizosphere soil was changed by applying more than 3% biochar. Among the relatively abundant dominant phyla, Gemmatimonadetes, Anaerolineae, Deltaproteobacteria and Verrucomicrobiae were reduced, and Alphaproteobacteria, Gammaproteobacteria, Bacteroidia, and Acidimicrobiia relative abundance increased. Furthermore, adding 3% biochar reduced the relative abundance of Gemmatimonas and increased the relative abundances of Ilumatobacter, Luteolibacter, Lysobacter, Arthrobacter, and Mesorhizobium. The nitrate content was positively correlated with the abundance of Gemmatimonadetes, and the nitrate content was significantly negatively correlated with the relative abundance of Ilumatobacter. Carbohydrate transport and metabolism in the rhizosphere soil of pakchoi decreased, and lipid transport and metabolism increased after biochar application.

Conclusion

Overall, our results indicated that applying biochar improved soil physicochemical states and plant nutrient absorption, and affected the abundance of dominant bacterial groups (e.g., Gemmatimonadetes and Ilumatobacter), these were the main factors to increase pakchoi growth and promote quality of pakchoi. Therefore, considering the growth, quality of pakchoi, and soil environment, the effect of using 3% biochar is better.

Comparative and functional analysis unveils the contribution of photoperiod to DNA methylation, sRNA accumulation, and gene expression variations in short-day and long-day grasses

Photoperiod employs complicated networks to regulate various developmental processes in plants, including flowering transition. However, the specific mechanisms by which photoperiod affects epigenetic modifications and gene expression variations in plants remain elusive. In this study, we conducted a comprehensive analysis of DNA methylation, small RNA (sRNA) accumulation, and gene expressions under different daylengths in facultative long-day (LD) grass Brachypodium distachyon and short-day (SD) grass rice. Our results showed that while overall DNA methylation levels were minimally affected by different photoperiods, CHH methylation levels were repressed under their favorable light conditions, particularly in rice. We identified numerous differentially methylated regions (DMRs) that were influenced by photoperiod in both plant species. Apart from differential sRNA clusters, we observed alterations in the expression of key components of the RNA-directed DNA methylation pathway, DNA methyltransferases, and demethylases, which may contribute to the identified photoperiod-influenced CHH DMRs. Furthermore, we identified many differentially expressed genes in response to different daylengths, some of which were associated with the DMRs. Notably, we discovered a photoperiod-responsive gene MYB11 in the transcriptome of B. distachyon, and further demonstrated its role as a flowering inhibitor by repressing FT1 transcription. Together, our comparative and functional analysis sheds light on the effects of daylength on DNA methylation, sRNA accumulation, and gene expression variations in LD and SD plants, thereby facilitating better designing breeding programs aimed at developing high-yield crops that can adapt to local growing seasons.

Auxochrome Dimethyl-Dihydroacridine Improves Fluorophores for Prolonged Live-Cell Super-Resolution Imaging

Superior photostability, minimal phototoxicity, red-shifted absorption/emission wavelengths, high brightness, and an enlarged Stokes shift are essential characteristics of top-tier organic fluorophores, particularly for long-lasting super-resolution imaging in live cells (e.g., via stimulated emission depletion (STED) nanoscopy). However, few existing fluorophores possess all of these properties. In this study, we demonstrate a general approach for simultaneously enhancing these parameters through the introduction of 9,9-dimethyl-9,10-dihydroacridine (DMA) as an electron-donating auxochrome. DMA not only induces red shifts in emission wavelengths but also suppresses photooxidative reactions and prevents the formation of triplet states in DMA-based fluorophores, greatly improving photostability and remarkably minimizing phototoxicity. Moreover, the DMA group enhances the fluorophores' brightness and enlarges the Stokes shift. Importantly, the "universal" benefits of attaching the DMA auxochrome have been exemplified in various fluorophores including rhodamines, difluoride-boron complexes, and coumarin derivatives. The resulting fluorophores successfully enabled the STED imaging of organelles and HaloTag-labeled membrane proteins.

Fluorogenic Rhodamine Probes with Pyrrole Substitution Enables STED and Lifetime Imaging of Lysosomes in Live Cells

Fluorogenic dyes with high brightness, large turn-on ratios, excellent photostability, favorable specificity, low cytotoxicity, and high membrane permeability are essential for high-resolution fluorescence imaging in live cells. In this study, we endowed these desirable properties to a rhodamine derivative by simply replacing the N, N-diethyl group with a pyrrole substituent. The resulting dye, Rh-NH, exhibited doubled Stokes shifts (54 nm) and a red-shift of more than 50 nm in fluorescence spectra compared to Rhodamine B. Rh-NH preferentially exists in a non-emissive but highly permeable spirolactone form. Upon binding to lysosomes, the collective effects of low pH, low polarity, and high viscosity endow Rh-NH with significant fluorescence turn-on, making it a suitable candidate for wash-free, high-contrast lysosome tracking. Consequently, Rh-NH enabled us to successfully explore stimulated emission depletion (STED) super-resolution imaging of lysosome dynamics, as well as fluorescence lifetime imaging of lysosomes in live cells.

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.

Measurement of the Centrality Dependence of the Dijet Yield in p+Pb Collisions at sqrt[s_{NN}]=8.16 TeV with the ATLAS Detector

ATLAS measured the centrality dependence of the dijet yield using 165  nb^{-1} of p+Pb data collected at sqrt[s_{NN}]=8.16  TeV in 2016. The event centrality, which reflects the p+Pb impact parameter, is characterized by the total transverse energy registered in the Pb-going side of the forward calorimeter. The central-to-peripheral ratio of the scaled dijet yields, R_{CP}, is evaluated, and the results are presented as a function of variables that reflect the kinematics of the initial hard parton scattering process. The R_{CP} shows a scaling with the Bjorken x of the parton originating from the proton, x_{p}, while no such trend is observed as a function of x_{Pb}. This analysis provides unique input to understanding the role of small proton spatial configurations in p+Pb collisions by covering parton momentum fractions from the valence region down to x_{p}∼10^{-3} and x_{Pb}∼4×10^{-4}.

Nicotinamide protects against diabetic kidney disease through regulation of Sirt1

PURPOSE

To investigate the effect of nicotinamide (Nam) on diabetic kidney disease (DKD) in mice and explore its mechanism.

METHODS

Thirty DBA/2 J mice were randomly assigned to three groups. After 8 weeks of hyperglycemia induced by streptozocin (STZ), Nam and saline were administrated to STZ + Nam and STZ + NS mice, respectively, for 8 weeks. Non-diabetic mice (NDM) were used as control group. Twenty In2-/- Akita mice were randomly divided into two groups. After 8 weeks of hyperglycemia, Nam and saline were administered to Akita + Nam and Akita + NS mice, respectively, for 6 weeks. Wild-type littermates were used as control group. Markers of renal injury were analyzed, and the molecular mechanisms were explored in human proximal tubular HK2 cells.

RESULTS

Urinary albumin-to-creatinine ratio (UACR) and kidney injury molecule 1 (KIM-1) decreased in the STZ + Nam and Akita + Nam groups. Pathological analysis showed that Nam improved the structure of glomerular basement membrane, ameliorated glomerular sclerosis, and decreased the accumulation of extracellular matrix and collagen. Compared to the diabetic control group, renal fibrosis, inflammation, and oxidative stress were reduced in the Nam-treated mice. The expression of sirtuin 1 (Sirt1) in human proximal tubular HK2 cells was inhibited by high glucose and Nam treatment enhanced its expression. However, in HK2 cells with Sirt1 knockdown, the protective effect of Nam was abolished, indicating that the beneficial effect of Nam was partially dependent on Sirt1.

CONCLUSIONS

Nam has a renoprotective effect against renal injury caused by hyperglycemia and may be a potential target for the treatment of DKD.

Individualized brain mapping for navigated neuromodulation

ABSTRACT

The brain is a complex organ that requires precise mapping to understand its structure and function. Brain atlases provide a powerful tool for studying brain circuits, discovering biological markers for early diagnosis, and developing personalized treatments for neuropsychiatric disorders. Neuromodulation techniques, such as transcranial magnetic stimulation and deep brain stimulation, have revolutionized clinical therapies for neuropsychiatric disorders. However, the lack of fine-scale brain atlases limits the precision and effectiveness of these techniques. Advances in neuroimaging and machine learning techniques have led to the emergence of stereotactic-assisted neurosurgery and navigation systems. Still, the individual variability among patients and the diversity of brain diseases make it necessary to develop personalized solutions. The article provides an overview of recent advances in individualized brain mapping and navigated neuromodulation and discusses the methodological profiles, advantages, disadvantages, and future trends of these techniques. The article concludes by posing open questions about the future development of individualized brain mapping and navigated neuromodulation.

Risk of metastasis and survival in patients undergoing different treatment strategies with T1 colonic neuroendocrine tumors

PURPOSE

The efficacy and safety of local excision (LE) for small (< 1‒2 cm) colonic neuroendocrine tumors (NETs) is controversial due to the higher metastasis risk when compared with rectal NETs. The study aimed to evaluate the metastasis risk of T1 colonic NETs and compare patients' long-term prognosis after LE or radical surgery (RS).

METHODS

The Surveillance Epidemiology and End Results database was used to identify patients with T1 colonic NETs (2004‒2015). Multivariable logistic regression was performed to assess factors associated with metastasis risk. Propensity score matching was used to balance the variables. Cancer-specific survival (CSS) and overall survival (OS) were calculated to estimate the prognosis of patients with T1N0M0 colonic NETs who underwent LE or RS.

RESULTS

Of the 610 patients with colonic NETs, 46 (7.54%) had metastasis at diagnosis. Tumor size (11-20 mm) (OR = 9.51; 95% confidence interval (CI): 4.32‒21.45; P < 0.001), right colon (OR = 15.79; 95% CI 7.20‒38.56; P < 0.001), submucosal infiltration (OR = 2.08; 95% CI 0.84‒5.57; P = 0.125) were independent risk factors associated with metastasis. Of the 515 patients with T1N0M0 colonic NETs, the overall long-term prognosis of LE was as good as that of RS groups (after matching, 5-year CSS: 97.9% vs. 94.6%, P = 0.450; 5-year OS: 92.7% vs. 85.6%, P = 0.009).

CONCLUSION

Tumor size (11‒20 mm) and site (right colon) are associated with metastasis in T1 colonic NETs. In the absence of metastasis, LE could be a viable option for 0‒10 mm T1 colonic NETs with well/moderate differentiation in the left colon in terms of long-term survival.

Physiological, transcriptome and gene functional analysis provide novel sights into cadmium accumulation and tolerance mechanisms in kenaf

Kenaf is considered to have great potential for remediation of heavy metals in ecosystems. However, studies on molecular mechanisms of root Cd accumulation and tolerance are still inadequate. In this study, two differently tolerant kenaf cultivars were selected as materials and the physiological and transcriptomic effects were evaluated under Cd stress. This study showed that 200 µmol/L CdCl2 treatment triggered the reactive oxygen species (ROS) explosion and membrane lipid peroxidation. Compared with the Cd-sensitive cultivar 'Z', the Cd-tolerant cultivar 'F' was able to resist oxidative stress in cells by producing higher antioxidant enzyme activities and increasing the contents of ascorbic acid (AsA) and glutathione (GSH). The root cell wall of 'F' exhibited higher polysaccharide contents under Cd treatment, providing more Cd-binding sites. There were 3,439 differentially expressed genes (DEGs) that were co-regulated by Cd treatment in two cultivars. Phenylpropanoid biosynthesis and plant hormone signal transduction pathways were significantly enriched by functional annotation analysis. DEGs associated with pectin, cellulose, and hemi-cellulose metabolism were involved in Cd chelation of root cell wall; V-ATPases, ABCC3 and Narmp3 could participated in vacuolar compartmentalization of Cd; PDR1 was responsible for Cd efflux; the organic acid transporters contributed to the absorption of Cd in soil. These genes might have played key roles in kenaf Cd tolerance and Cd accumulation. Moreover, HcZIP2 was identified to be involved in Cd uptake and transport in kenaf. Our findings provide a deeper understanding of the molecular pathways underlying Cd accumulation and detoxification mechanisms in kenaf.

Efficacy and safety of the Latarjet procedure for the treatment of athletes with glenoid bone defects ≥ 20%: a single-arm meta-analysis

BACKGROUND

The shoulder joint is the most commonly dislocated joint in the human body, and the recurrence rate exceeds 50% after nonsurgical treatment. Although surgical treatment reduces the recurrence rate, there is controversy regarding the optimal surgical approach. Previous studies suggest that the Latarjet procedure yields favourable outcomes for specific populations at risk of recurrence, such as competitive athletes with significant glenoid defects. However, most of the existing related research consists of nonrandomized controlled trials with small sample sizes, and there is a lack of strong evidence regarding the efficacy and safety of the Latarjet procedure.

METHODS

The PubMed, Embase, Cochrane Library, and Web of Science databases were systematically searched. Athletes with ≥ 20% glenoid defects were selected for inclusion. The following data were extracted: general patient information, instability rates, return to sports (RTS) rates, imaging features (graft positioning rate and graft healing rate), functional assessments [Rowe score, Athletic Shoulder Outcome Scoring System(ASOSS), visual analogue scale (VAS), forward flexion function, and external rotation function], and complications.

RESULTS

After excluding suspected duplicate cases, a total of 5 studies were included in this meta-analysis. The studies involved a total of 255 patients, including 237 males (93%) and 18 females (7%). The average age at the time of surgery was 25.4 ± 8.5 years. All the studies had a minimum follow-up period of 2 years, with an average follow-up time of 48.7 ± 18.9 months. The pooled rate of return to sport (RTS) was 94.3% (95% CI: 87.3%, 98.8%), and 86.1% (95% CI: 78.2%, 92.5%) of patients returned to their preoperative level of activity. The pooled redislocation rate was 1.1% (95% CI: 0%, 3.8%). Regarding the imaging results, the combined graft retention rate was 92.1% (95% CI: 88.1%, 95.5%), and the graft healing rate was 92.1% (95% CI: 88%, 95.4%). Postoperative functional evaluation revealed that the combined Rowe score, ASOSS score, and VAS score were 93.7 ± 6.5 points, 88.5 ± 4.4 points, and 1.1 ± 10 points, respectively. The forward flexion and external rotation angles were 170.9 ± 6.9 degrees and 65.6 ± 4.5 degrees, respectively. After excluding one study with unclear complications, the combined complication rate was 9.4% (95% CI: 1.0%, 23.6%).

CONCLUSION

For athletes with shoulder instability and a total of ≥ 20% glenoid bone defects, the Latarjet procedure can achieve excellent functional outcomes, with the majority of patients returning to preoperative levels of sports activity. This procedure also leads to a low recurrence rate. Therefore, the Latarjet procedure has been proven to be a safe and effective treatment.

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.

RNA-Seq analysis reveals the mechanism in response to cold stress of peach cv 'Dingjiaba'

BACKGROUND

'Dingjiaba' is an important Prunus persica cultivar (cv) mainly grown in the Hexi corridor in northwest China, which has an inherited strong cold tolerance.

OBJECTIVE

To compare the transcriptome and physiology data of leaves of cvs 'Dingjiaba' (D) and 'Kanoiwa' (K) following cold treatment at different time periods, in order to gain new insights into the mechanisms of cold adaptation in 'Dingjiaba'.

MATERIALS AND METHODS

We analyzed the transcriptomic and physiological data of leaves of D and K cvs exposed to 0 h (D0/K0), 2 h (D2/K2), 6 h (D6/K6) and 12 h (D12/K12) cold stress.

RESULTS

Low temperature stress caused membrane damage and led to increased rate of electrolyte leakage and increased MDA content. Cold stress induced the accumulation of soluble sugars, soluble proteins and proline in leaves of both cvs, with a lower increase in K compared to D. Transcriptome analysis identified 4,631, 5,069, 5,662 and 3,886 differentially expressed genes (DEGs) between D0 and K0, D2 and K2, D6 and K6 and D12 and K12, respectively. The differentially expressed genes significantly enriched in metabolic pathways and biosynthesis of secondary metabolites. We further validated the reliability of sequencing data of the RNA-Seq with Real-Time Quantitative PCR, which suggested that the expression trend of the RNA-Seq were same as RT-PCR.

CONCLUSIONS

These results provide novel insights into a series of molecular mechanisms underlying physiological metabolism and defense. https://doi.org/10.54680/fr24210110312.

Risk factors of cognitive frailty in elderly chronic obstructive pulmonary disease patients and its implication for death: a cohort study

BACKGROUNDS

Cognitive frailty, a clinical syndrome with physical frailty and cognitive impairment, leads to mortality and other adverse health outcomes in older adults. This study aimed to investigate the prevalence of cognitive frailty, and its influencing factors, and follow its impact on short-term mortality in elderly chronic obstructive pulmonary disease patients, to provide a theoretical scientific reference basis for clinical intervention and management of cognitive frailty.

METHODS

A sample of 243 elderly chronic obstructive pulmonary disease patients in the respiratory department of a tertiary care hospital was conveniently sampled from November 2021 to February 2023, and the prevalence of cognitive frailty was investigated using the General Information Survey Scale, the Fried Phenotype Scale, the Mini-Mental State Examination, the Anxiety Self-Rating Scale, the Brief Geriatric Depression Scale, and the Mortality Record. The mortality was recorded by telephone follow-up after 6 months. A database was created and statistical analysis such as one-way analysis of variance, logistic regression analysis, Kaplan-Meier, and Cox survival analysis were used to analyze the data.

RESULTS

A total of 47 patients (19.3%) had cognitive frailty; there were statistical differences in the prevalence of cognitive frailty by medical payment type, physical exercise, and sleeping time (P < 0.05). During a 6-month follow-up, 38 patients (15.6%) died. Cox survival analysis showed that the risk of death in elderly chronic obstructive pulmonary disease patients in the cognitive frailty group was 3.212 times higher than that in the normal cognitive function and non-frailty group (95% CI 1.646-6.270, P = 0.001), and 5.266 times higher than that in the normal cognitive function and frailty group (95% CI 3.159-8.778, P < 0.001).

CONCLUSIONS

The prevalence of cognitive frailty in elderly chronic obstructive pulmonary disease patients is high, and clinical staff should pay attention to patients' medical burden and financial ability, and reduce the incidence of cognitive frailty by instructing patients to perform physical exercise and arrange sleep time. Cognitive frailty is an important risk factor for mortality within 6 months in elderly chronic obstructive pulmonary disease patients, and early intervention should be emphasised to reduce or delay cognitive frailty and mortality.

Simultaneous determination of HD56, a novel prodrug, and its active metabolite in cynomolgus monkey plasma using LC-MS/MS for elucidating its pharmacokinetic profile

An LC-MS/MS method was developed and validated for the simultaneous determination of the carboxylic acid ester precursor HD56 and the active product HD561 in cynomolgus monkey plasma. Then, the pharmacokinetic characteristics of both compounds following single and multiple i.g. administrations in cynomolgus monkeys were elucidated. In the method, chromatographic separation was achieved with a C18 reversed-phase column and the target quantification was carried out by an electrospray ionization (ESI) source coupled with triple quadrupole mess detector in positive ionization mode with multiple reaction monitoring (MRM) approach. Using the quantification method, the in vitro stability of HD56 in plasma and HD56 pharmacokinetic behavior after i.g. administration in cynomolgus monkey were investigated. It was approved that HD56 did convert into HD561 post-administration. The overall systemic exposure of HD561 post-conversion from HD56 accounted for only about 17% of HD56. After repeated administration at the same dose, there was no significant difference in exposure levels of both HD56 and HD561. However, after multiple dosing, the exposure of HD56 tended to decrease while that of HD561 tended to increase, resulting in a 30% in the exposure ratio. Remarkably, with a carboxylesterase (CES) activity profile akin to humans, the observed in vivo pharmacokinetic profile in cynomolgus monkeys holds promise for predicting HD56/HD561 PK profiles in humans.

Prior-guided individualized thalamic parcellation based on local diffusion characteristics

Comprising numerous subnuclei, the thalamus intricately interconnects the cortex and subcortex, orchestrating various facets of brain functions. Extracting personalized parcellation patterns for these subnuclei is crucial, as different thalamic nuclei play varying roles in cognition and serve as therapeutic targets for neuromodulation. However, accurately delineating the thalamic nuclei boundary at the individual level is challenging due to intersubject variability. In this study, we proposed a prior-guided parcellation (PG-par) method to achieve robust individualized thalamic parcellation based on a central-boundary prior. We first constructed probabilistic atlas of thalamic nuclei using high-quality diffusion MRI datasets based on the local diffusion characteristics. Subsequently, high-probability voxels in the probabilistic atlas were utilized as prior guidance to train unique multiple classification models for each subject based on a multilayer perceptron. Finally, we employed the trained model to predict the parcellation labels for thalamic voxels and construct individualized thalamic parcellation. Through a test-retest assessment, the proposed prior-guided individualized thalamic parcellation exhibited excellent reproducibility and the capacity to detect individual variability. Compared with group atlas registration and individual clustering parcellation, the proposed PG-par demonstrated superior parcellation performance under different scanning protocols and clinic settings. Furthermore, the prior-guided individualized parcellation exhibited better correspondence with the histological staining atlas. The proposed prior-guided individualized thalamic parcellation method contributes to the personalized modeling of brain parcellation.

Exploring the potential mechanism of Heng-Gu-Gu-Shang-Yu-He-Ji therapy for osteoporosis based on network pharmacology and transcriptomics

ETHNOPHARMACOLOGICAL RELEVANCE

Heng-Gu-Gu-Shang-Yu-He-Ji (Osteoking, OK) is a well-known formula for fracture therapy. In clinic, OK is effective in treating fractures while alleviating osteoporosis (OP) symptoms. However, active components of OK and the associated molecular mechanisms remain not fully elucidated.

AIM OF THE STUDY

This study aims to systematically evaluate the anti-osteoporosis efficacy of OK and for the first time combine network pharmacology with high-throughput whole gene transcriptome sequencing to study its underlying mechanism.

MATERIALS AND METHODS

In this study, the osteoporosis model was established by the castration of both ovaries. The level of serum bone turnover factor was detected by enzyme-linked immunosorbent assay. Micro-CT and HE staining were used to observe the changes of bone histopathology, and nano-indentation technique was used to detect the biomechanical properties of rat bone. The main active Chemical components of OK were identified using UPLC-DAD. Efficacy verification and mechanism exploration were conducted by network pharmacology, molecular docking, whole gene transcriptomics and in vivo experiments.

RESULTS

In our study, OK significantly improved bone microarchitecture and bone biomechanical parameters in OVX rats, reduced osteoclast indexes such as C-telopeptide of type I collage (CTX-I) and increased Osteoprotegerin (OPG)/Receptor activator of NF-κB ligand (RANKL) levels. Mechanistically, PI3K/AKT pathway was a common pathway for genome enrichment analysis (KEGG) of both network pharmacology and RNA-seq studies. G protein-β-like protein (GβL), Ribosomal-protein S6 kinase homolog 2 (S6K2), and Phosphoinositide 3-kinase (PI3K) appeared differentially expression in the PI3K-AKT signaling pathway. These results were also confirmed by qRT-PCR and immunohistochemistry.

CONCLUSIONS

OK may be used to treat osteoporosis, at least partly by activating PI3K/AKT/mTORC1 signaling pathway.

Age effect on the shared etiology of glycemic traits and serum lipids: evidence from a Chinese twin study

PURPOSE

Diabetes and dyslipidemia are among the most common chronic diseases with increasing global disease burdens, and they frequently occur together. The study aimed to investigate differences in the heritability of glycemic traits and serum lipid indicators and differences in overlapping genetic and environmental influences between them across age groups.

METHODS

This study included 1189 twin pairs from the Chinese National Twin Registry and divided them into three groups: aged ≤ 40, 41-50, and > 50 years old. Univariate and bivariate structural equation models (SEMs) were conducted on glycemic indicators and serum lipid indicators, including blood glucose (GLU), glycated hemoglobin A1c (HbA1c), total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C), in the total sample and three age groups.

RESULTS

All phenotypes showed moderate to high heritability (0.37-0.64). The heritability of HbA1c demonstrated a downward trend with age (HbA1c: 0.50-0.79), while others remained relatively stable (GLU: 0.55-0.62, TC: 0.58-0.66, TG: 0.50-0.63, LDL-C: 0.24-0.58, HDL-C: 0.31-0.57). The bivariate SEMs demonstrated that GLU and HbA1c were correlated with each serum lipid indicator (0.10-0.17), except HDL-C. Except for HbA1c and LDL-C, as well as HbA1c and HDL-C, differences in genetic correlations underlying glycemic traits and serum lipids between age groups were observed, with the youngest group showing a significantly higher genetic correlation than the oldest group.

CONCLUSION

Across the whole adulthood, genetic influences were consistently important for GLU, TC, TG, LDL-C and HDL-C, and age may affect the shared genetic influences between glycemic traits and serum lipids. Further studies are needed to elucidate the role of age in the interactions of genes related to glycemic traits and serum lipids.

Effects of butyl paraben on behavior and molecular mechanism of Chinese striped-necked turtle (Mauremys sinensis)

Butyl paraben (BuP) is widely used in cosmetics, drugs, and food preservation. Recently it is an identified new pollutant that affects various aspects of reproduction, lipid metabolism, and nervous system. Behavioral activity serves as a pre-warning biomarker for predicting water quality. So, in this study, the changes in some behaviors and its neurotransmitters and cell apoptosis in the brain of Chinese striped-necked turtles (Mauremys sinensis) were studied when the turtles were exposed to BuP concentrations of 0, 5, 50, 500, and 5000 µg/L for 21 weeks. The results showed that, the basking time and altering scores to external stimuli in the groups of 50, 500, and 5000 µg/L were significantly reduced, while the time for body-righting was significantly increased, compared with the control (0 µg/L), indicating that the turtles exhibited depression and inactive behavior. The analysis of neurotransmitter in the brain showed that 5-hydroxytryptamine (5-HT) contents in the groups of 500 and 5000 µg/L were significantly higher than the other groups, which was due to an increase in the mRNA relative expression levels of the 5-HT receptor gene (5-HTR), neurotransmitter transporter genes (Drd4, Slc6a4), and neurotransmitter synthase tryptophan hydroxylase (TPH). Furthermore, GABA transaminase (GABA-T) activity increased in the 500 and 5000 µg/L groups, and tyrosine hydroxylase (TH) activity increased dramatically in the 5000 µg/L group. However, acetyl-CoA (AChE) activity was significantly reduced in these four BuP exposure groups. These changes could be attributed to decreased movement velocity and increased inactivity. Meanwhile, the mRNA expression level of BAX, Bcl-2, caspase-9 and TUNEL assay indicated the occurrence of cell apoptosis in the brains of the higher BuP exposed groups, which may play an important role in neuronal death inducing behavior change. In summary, these findings offer fundamental insights into turtle ecotoxicology and serve as a foundation for a comprehensive assessment of the ecological and health risks associated with BuP.

Real-world effectiveness of cytology and HPV-based screening strategy in cervical cancer screening: A cross-sectional population-based study in Chengdu, China

Cervical cancer poses a significant health challenge in developing countries, emphasizing the need for appropriate screening strategies to accelerate the elimination of this disease. This study summarized the results of a large-scale community-based cervical cancer screening program conducted in Chengdu, China, to understand the prevalence of HPV infection and cervical lesions in the population, and to compare the real-world effectiveness of two different screening methods implemented in the program. From January 2021 to December 2022, a total of 363,376 women aged 35-64 years in Chengdu received free screenings. Among these participants, 70.1% received cytology screening and 29.9% received HPV testing combined with 16/18 genotyping and cytology triage. Ultimately, 824 cases of high-grade lesions and cervical cancer were detected, with a total detection rate of cervical cancer and precancerous lesions of 226.8 per 100,000. The follow-up rate of patients with high-grade lesions and above was 98.9%, and the treatment rate was 86.6%. The overall high-risk HPV infection rate was 11.7%, with the HPV 16/18 infection rate of 1.4%. The rate of abnormal cytology results was 2.8%. The attendance rates for colposcopy and histopathology were 71.6% and 86.1%, respectively. By calculating the age-standardized rates to eliminate the different age composition between the two group, the HPV-based screening strategy had a higher rate of primary screening abnormalities (3.4% vs. 2.8%, P<0.001), higher attendance rates of colposcopy (76.5% vs. 68.9%, P<0.001) and histopathological diagnosis (94.1% vs. 78.0%, P<0.001), higher percentage of abnormal colposcopy results (76.0% vs. 44.0%, P<0.001), and higher detection rate of cervical precancerous lesions and cancer (393.1 per 100,000 vs. 156.4 per 100,000, P<0.001) compared to cytology screening. Our study indicates that the combination of HPV testing with 16/18 genotyping and cytology triage has demonstrated superior performance in cervical cancer screening compared to cytology alone in large-scale population.

Interfacial π-p Electron Coupling Prompts Hydrogen Evolution Reaction Activity in Acidic Electrolyte

The thermodynamically stable 2H-phase MoS2 is a brilliant material toward hydrogen evolution reaction (HER) owing to its excellent Gibbs free energy of hydrogen adsorption. Nevertheless, the poor intrinsic properties of 2H-MoS2 limit its electrocatalytic performances toward HER. In this work, graphitic carbon nitride covalently bridging 2H-MoS2 (MoS2/GCN) is proposed to construct robust HER electrocatalysts. The strong π-p electron coupling between the delocalized π electrons of GCN and the localized p electrons of S atoms sufficiently expose active sites and accelerate the reaction kinetics. To be specific, MoS2/GCN exhibits remarkable HER activity (160 mV at 10 mA·cm-2) and long-term durability. Importantly, MoS2/GCN also provides great potential for industrial application. Density functional theory (DFT) calculations disclose that the π-p electron coupling at the MoS2/GCN interface regulates the electronic structure of S atoms, consequently providing enhanced HER performance. This work presents a feasible pathway to develop advanced electrocatalysts for energy conversions.

Search for New Phenomena in Two-Body Invariant Mass Distributions Using Unsupervised Machine Learning for Anomaly Detection at sqrt[s]=13 TeV with the ATLAS Detector

Searches for new resonances are performed using an unsupervised anomaly-detection technique. Events with at least one electron or muon are selected from 140  fb^{-1} of pp collisions at sqrt[s]=13  TeV recorded by ATLAS at the Large Hadron Collider. The approach involves training an autoencoder on data, and subsequently defining anomalous regions based on the reconstruction loss of the decoder. Studies focus on nine invariant mass spectra that contain pairs of objects consisting of one light jet or b jet and either one lepton (e,μ), photon, or second light jet or b jet in the anomalous regions. No significant deviations from the background hypotheses are observed. Limits on contributions from generic Gaussian signals with various widths of the resonance mass are obtained for nine invariant masses in the anomalous regions.

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.

Sevoflurane Alters Serum Metabolites in Elders and Aging Mice and Increases Inflammation in Hippocampus

Purpose

Postoperative cognitive dysfunction (POCD) is a central nervous system complication that occurs after anesthesia, particularly among the elderly. However, the neurological pathogenesis of postoperative cognitive dysfunction remains unclear. The aim of this study was to evaluate the effects of sevoflurane exposure on serum metabolites and hippocampal gene expression in elderly patients and aging mice by metabolomics and transcriptomic analysis and to explore the pathogenesis of sevoflurane induced POCD.

Patients and Methods

Human serum samples from five patients over 60 years old were collected before sevoflurane anesthesia and 1 hour after anesthesia. Besides, mice aged at 12 months (n=6 per group) were anesthetized with sevoflurane for 2 hours or with sham procedure. Subsequently, serum and hippocampal tissues were harvested for analysis. Further investigation into the relationship between isatin and neuroinflammation was conducted using BV2 microglial cells.

Results

Sevoflurane anesthesia led to the activation of inflammatory pathways, an increased presence of hippocampal astrocytes and microglia, and elevated expression of neuroinflammatory cytokines. Comparative analysis identified 12 differential metabolites that exhibited changes in both human and mouse serum post-sevoflurane anesthesia. Notably, isatin levels were significantly decreased after anesthesia. Notably, isatin levels significantly decreased after anesthesia, a factor known to stimulate proliferation and proinflammatory gene expression in microglia-the pivotal cell type in inflammatory responses.

Conclusion

Sevoflurane-induced alterations in serum metabolites in both elderly patients and aging mice, subsequently contributing to increased inflammation in the hippocampus.

A tryst of 'blood pressure control- sex- comorbidities': the odyssey of basic public health services in Yunnan in quest for truth

BACKGROUND

The Basic Public Health Service (BPHS), a recently announced free healthcare program, aims to combat the most prevalent Noncommunicable Disease-"Hypertension" (HTN)-and its risk factors on a nationwide scale. In China, there is a rife that HTN less impacts women during their lifetime. We, therefore, aimed to evaluate the sex disparity in hypertension patients with comorbidities among south-west Chinese and the contribution of BPHS to address that concern.

METHODS

We have opted for a multistage stratified random sampling method to enroll hypertensive patients of 35 years and older, divided them into BPHS and non-BPHS groups. We assessed the sex disparity in HTN patients with four major comorbidities- Dyslipidemia, Diabetes Mellitus (DM), Cardiovascular Disease (CVD), and Chronic Kidney Disease (CKD), and descriptive data were compiled. Odds ratios from logistic regression models estimated the effectiveness of BPHS in the management of HTN with comorbidities.

RESULTS

Among 1521 hypertensive patients,1011(66.5%) were managed in the BPHS group. The proportion of patients who had at least one comorbidity was 70.7% (95% confidence interval [CI]: 66.3-76.8%), patients aged 65 years and older were more likely to have coexisting comorbidities. Participants who received the BPHS showed significant blood pressure (BP) control with two comorbidities (odds ratio [OR] = 2.414, 95% CI: 1.276-4.570), three or more (OR = 5.500, 95%CI: 1.174-25.756). Patients with dyslipidemia and DM also benefited from BPHS in controlling BP (OR = 2.169, 95% CI: 1.430-3.289) and (OR = 2.785, 95%CI: 1.242-6.246), respectively. In certain high-income urban survey centers, there was sex differences in the HTN management provided by BPHS, with men having better BP control rates than women.

CONCLUSIONS

Perhaps this is the first study in China to succinctly show the effectiveness and sex disparity regarding "management of hypertensive comorbidities". This supports that the BPHS program plays a pivotal role in controlling BP, therefore should recommend the national healthcare system to give women a foremost priority in BPHS, especially to those from low-socioeconomic and low-scientific literacy regions.

Colon-targeted piperine-glycyrrhizic acid nanocrystals for ulcerative colitis synergetic therapy via macrophage polarization

Ulcerative colitis (UC) is a chronic inflammatory disease that affects the gastrointestinal tract and is characterized by immune dysregulation. Oral administration of nanoformulations containing immunomodulators is a desirable approach to treating UC. However, low drug-loading (<10%, typically), premature drug release, and systemic absorption of these nanoformulations continue to be significant challenges restricting clinical applications. Herein, we developed colon-targeted piperine-glycyrrhizic acid nanocrystals (ES100-PIP/GA NCs) to treat UC through the regulation of macrophages. The ES100-PIP/GA NCs exhibited ultra-high drug loading and colon-specific drug release. In vitro studies demonstrated that the ES100-PIP/GA NCs could effectively be internalized by lipopolysaccharide (LPS)-induced RAW 264.7 and Caco-2 cells. More importantly, the ES100-PIP/GA NCs could downregulate pro-inflammatory factors (IL-1β, IL-17A), upregulate anti-inflammatory factors (TGF-β1), and repair the intestinal mucosal barrier. In a murine model of acute colitis induced by dextran sodium sulfate (DSS), ES100-PIP/GA NCs could protect PIP and GA from gastric acid destruction, reach the colon, and significantly inhibit colitis. Surprisingly, ES100-PIP/GA NCs enhance M2 macrophages by increasing the mammalian target of rapamycin (mTOR), and inhibit M1 macrophages by reducing hypoxia-inducible factor-1α (HIF-1α). Overall, this study shows that ES100-PIP/GA NCs have synergistic immunotherapy capabilities with macrophage regulation, which offers a promising blueprint for the oral delivery of multicomponent drugs in UC therapy.

The impact of internal-generated contextual clues on EFL vocabulary learning: insights from EEG

With the popularity of learning vocabulary online among English as a Foreign Language (EFL) learners today, educators and researchers have been considering ways to enhance the effectiveness of this approach. Prior research has underscored the significance of contextual clues in vocabulary acquisition. However, few studies have compared the context provided by instructional materials and that generated by learners themselves. Hence, this present study sought to explore the impact of internal-generated contextual clues in comparison to those provided by instructional materials on EFL learners' online vocabulary acquisition. A total of 26 university students were enrolled and underwent electroencephalography (EEG). Based on a within-subjects design, all participants learned two groups of vocabulary words through a series of video clips under two conditions: one where the contexts were externally provided and the other where participants themselves generated the contexts. In this regard, participants were tasked with either viewing contextual clues presented on the screen or creating their own contextual clues for word comprehension. EEG signals were recorded during the learning process to explore neural activities, and post-tests were conducted to assess learning performance after each vocabulary learning session. Our behavioral results indicated that comprehending words with internal-generated contextual clues resulted in superior learning performance compared to using context provided by instructional materials. Furthermore, EEG data revealed that learners expended greater cognitive resources and mental effort in semantically integrating the meaning of words when they self-created contextual clues, as evidenced by stronger alpha and beta-band oscillations. Moreover, the stronger alpha-band oscillations and lower inter-subject correlation (ISC) among learners suggested that the generative task of creating context enhanced their top-down attentional control mechanisms and selective visual processing when learning vocabulary from videos. These findings underscored the positive effects of internal-generated contextual clues, indicating that instructors should encourage learners to construct their own contexts in online EFL vocabulary instruction rather than providing pre-defined contexts. Future research should aim to explore the limits and conditions of employing these two types of contextual clues in online EFL vocabulary learning. This could be achieved by manipulating the quality and understandability of contexts and considering learners' language proficiency levels.

Using machine learning to predict the bleeding risk for patients with cardiac valve replacement treated with warfarin in hospitalized

BACKGROUND

Distinguishing warfarin-related bleeding risk at the bedside remains challenging. Studies indicate that warfarin therapy should be suspended when international normalized ratio (INR) ≥ 4.5, or it may sharply increase the risk of bleeding. We aim to develop and validate a model to predict the high bleeding risk in valve replacement patients during hospitalization.

METHOD

Cardiac valve replacement patients from January 2016 to December 2021 across Nanjing First Hospital were collected. Five different machine-learning (ML) models were used to establish the prediction model. High bleeding risk was an INR ≥4.5. The area under the receiver operating characteristic curve (AUC) was used for evaluating the prediction performance of different models. The SHapley Additive exPlanations (SHAP) was used for interpreting the model. We also compared ML with ATRIA score and ORBIT score.

RESULTS

A total of 2376 patients were finally enrolled in this model, 131 (5.5%) of whom experienced the high bleeding risk after anticoagulation therapy of warfarin during hospitalization. The extreme gradient boosting (XGBoost) exhibited the best overall prediction performance (AUC: 0.882, confidence interval [CI] 0.817-0.946, Brier score, 0.158) compared to other prediction models. It also shows superior performance compared with ATRIA score and ORBIT score. The top 5 most influential features in XGBoost model were platelet, thyroid stimulation hormone, body surface area, serum creatinine and white blood cell.

CONCLUSION

A model for predicting high bleeding risk in valve replacement patients who treated with warfarin during hospitalization was successfully developed by using machine learning, which may well assist clinicians to identify patients at high risk of bleeding and allow timely adjust therapeutic strategies in evaluating individual patient.

Piperine improves levodopa availability in the 6-OHDA-lesioned rat model of Parkinson's disease by suppressing gut bacterial tyrosine decarboxylase

AIM

Tyrosine decarboxylase (TDC) presented in the gut-associated strain Enterococcus faecalis can convert levodopa (L-dopa) into dopamine (DA), and its increased abundance would potentially minimize the availability and efficacy of L-dopa. However, the known human decarboxylase inhibitors are ineffective in this bacteria-mediated conversion. This study aims to investigate the inhibition of piperine (PIP) on L-dopa bacterial metabolism and evaluates the synergistic effect of PIP combined with L-dopa on Parkinson's disease (PD).

METHODS

Metagenomics sequencing was adopted to determine the regulation of PIP on rat intestinal microbiota structure, especially on the relative abundance of E. faecalis. Then, the inhibitory effects of PIP on L-dopa conversion and TDC expression of E. faecalis were tested in vitro. We examined the synergetic effect of the combination of L-dopa and PIP on 6-hydroxydopamine (6-OHDA)-lesioned rats and tested the regulations of L-dopa bioavailability and brain DA level by pharmacokinetics study and MALDI-MS imaging. Finally, we evaluated the microbiota-dependent improvement effect of PIP on L-dopa availability using pseudo-germ-free and E. faecalis-transplanted rats.

RESULTS

We found that PIP combined with L-dopa could better ameliorate the move disorders of 6-OHDA-lesioned rats by remarkably improving L-dopa availability and brain DA level than L-dopa alone, which was associated with the effect of PIP on suppressing the bacterial decarboxylation of L-dopa via effectively downregulating the abnormal high abundances of E. faecalis and TDC in 6-OHDA-lesioned rats.

CONCLUSION

Oral administration of L-dopa combined with PIP can improve L-dopa availability and brain DA level in 6-OHDA-lesioned rats by suppressing intestinal bacterial TDC.