Fermented lily bulbs by "Jiangshui" probiotics improves lung health in mice

Limited application in protecting lung health is attributed to the low levels of active compounds in lily plant bulbs. This study focused on enhancing the active compounds by fermenting Lilium davidii (Lanzhou Lily) bulbs with Limosilactobacillus fermentum GR-3, isolated from Jiangshui. Lily fermented bulbs with strain GR-3 (LFB+GR-3) increased the bioavailability of hexadecanoic acid methyl ester, 22-tetrahydroxy-5alpha-cholestan-6-one-3-O-beta-d-allopyranoside, 22-O-(6-deoxy-Alpha-l-mannopyranosyl)-3-O-beta-d-glucopyranosyl-pregn-5-en-20-one, 1-O-trans-feruloylglycerol, and 3,4 dihydroxybenzoic acid. LFB+GR-3 fraction was employed to treat the mice model exposed to the carbon black nanoparticles (CBNPs). Immunohistochemical analysis revealed that the deposition of CBNPs and damages in lung tissues were limited in the LFB+GR-3 treatment group, while TNF-α, IL-10, and IL-6 were elevated by 6.9, 4.3, and 7 folds in the CBNP exposure group. In addition, Lactobacillus, Escherichia, Lactococcus, and Muribacter were dominant in the lung microbiota of LFB+GR-3 than the CBNP group. The use of probiotic fermented lily bulbs might be helpful in lung infection treatment.

Boosting Efficiency in Piezo-Photocatalysis Process Using Poled Ba0.7Sr0.3TiO3 Nanorod Arrays for Pollutant Degradation and Hydrogen Production

Recently, the combination of the piezoelectric effect in the photocatalytic process, referred to as piezo-photocatalysis, has gained considerable attention as a promising approach for enhancing the degradation of organic pollutants. In this investigation, we studied the piezo-photocatalysis by fabricating arrays of barium strontium titanate (Ba0.7Sr0.3TiO3) nanorods (BST NRs) on a glass substrate as recoverable catalysts. We found that the degradation rate constant k of the rhodamine B solution achieved 0.0447 min-1 using poled BST NRs in the piezo-photocatalytic process, indicating a 2-fold increase in efficiency compared to the photocatalytic process (0.00183 min-1) utilizing the same material. This is mainly ascribed to the generation of the piezopotential in the poled BST NRs under ultrasonic vibration. Moreover, the BST NR array demonstrated a hydrogen (H2) production rate of 411.5 μmol g-1 h-1. In the photoelectrochemical process, the photocurrent density of poled BST NRs achieved 1.97 mA cm-2 at an applied potential of 1.23 V (ERHE (reversible hydrogen electrode)) under ultrasonic vibrations, representing a 1.7-fold increase compared with the poled BST NRs without ultrasonic vibrations. The measurement results from the liquid chromatograph mass spectrometer (LC-MS) demonstrated the formulation of a degradation pathway for rhodamine B molecules. Moreover, ab initio molecular dynamics (AIMD) simulation results demonstrate the dominance of hydroxyl radicals (•OH) rather than superoxide radicals (•O2-) in the degradation process. This study not only benefits the understanding of the principle of the piezo-photocatalytic process but also provides a new perspective for improving the catalytic efficiency for organic pollutants degradation.

Study of association between corneal shape parameters and axial length elongation during orthokeratology using image-pro plus software

BACKGROUND

The aim was to validate the correlation between corneal shape parameters and axial length growth (ALG) during orthokeratology using Image-Pro Plus (IPP) 6.0 software.

METHODS

This retrospective study used medical records of myopic children aged 8-13 years (n = 104) undergoing orthokeratology. Their corneal topography and axial length were measured at baseline and subsequent follow-ups after lens wear. Corneal shape parameters, including the treatment zone (TZ) area, TZ diameter, TZ fractal dimension, TZ radius ratio, eccentric distance, pupil area, and pupillary peripheral steepened zone(PSZ) area, were measured using IPP software. The impact of corneal shape parameters at 3 months post-orthokeratology visit on 1.5-year ALG was evaluated using multivariate linear regression analysis.

RESULTS

ALG exhibited significant associations with age, TZ area, TZ diameter, TZ fractal dimension, and eccentric distance on univariate linear regression analysis. Multivariate regression analysis identified age, TZ area, and eccentric distance as significantly correlated with ALG (all P < 0.01), with eccentric distance showing the strongest correlation (β = -0.370). The regressive equation was y = 1.870 - 0.235a + 0.276b - 0.370c, where y represents ALG, a represents age, b represents TZ area, and c represents eccentric distance; R2 = 0.27). No significant relationships were observed between the TZ radius ratio, pupillary PSZ area, and ALG.

CONCLUSIONS

IPP software proves effective in capturing precise corneal shape parameters after orthokeratology. Eccentric distance, rather than age or the TZ area, significantly influences ALG retardation.

Synergistic analysis of lignin degrading bacterial consortium and its application in rice straw fiber film

Fiber film have received widespread attention due to its green friendliness. We can use microorganisms to degrade lignin in straw to obtain cellulose and make fiber films. Herein, a group of high-temperature (50 °C) lignin degrading bacterial consortium (LDH) was enriched and culture conditions for lignin degradation were optimized. Combined with high-throughput sequencing technology, the synergistic effect of LDH-composited bacteria was analyzed. Then LDH was used to treat rice straw for the bio-pulping experiment. The results showed that the lignin of rice straw was degraded 32.4 % by LDH at 50 °C for 10 d, and after the optimization of culture conditions, lignin degradation rate increased by 9.05 % (P < 0.001). The bacteria that compose in LDH can synergistically degrade lignin. Paenibacillus can encode all lignin-degrading enzymes present in the LDH. Preliminary tests of LDH in the pulping industry have been completed. This study is the first to use high temperature lignin degrading bacteria to fabricate fiber film.

YTHDC1 promotes the malignant progression of gastric cancer by promoting ROD1 translocation to the nucleus

RNA-binding proteins (RBPs) make vital impacts on tumor progression and are important potential targets for tumor treatment. Previous studies have shown that RBP regulator of differentiation 1 (ROD1), enriched in the nucleus, is abnormally expressed and functions as a splicing factor in tumors; however, the mechanism underlying its involvement in gastric cancer (GC) is unknown. In this study, ROD1 is found to stimulate GC cell proliferation and metastasis and is related to poor patient prognosis. In vitro experiments showed that ROD1 influences GC proliferation and metastasis through modulating the imbalance of the level of the oncogenic gene OIP5 and the tumor suppressor gene GPD1L. Further studies showed that the N6-methyladenosine (m6A) "reader" protein YTHDC1 can interact with ROD1 and regulate the balance of the expression of the downstream molecules OIP5/GPD1L by promoting the nuclear enrichment of ROD1. Therefore, YTHDC1 stimulates GC development and progression through modulating nuclear enrichment of the splicing factor ROD1.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Small extracellular vesicles facilitate epithelial-mesenchymal transition in chronic rhinosinusitis with nasal polyps via the miR-375-3p/QKI axis

BACKGROUND

Epithelial-mesenchymal transition (EMT) plays a crucial role in the pathogenesis of chronic rhinosinusitis with nasal polyps (CRSwNP). However, the involvement of small extracellular vesicles (sEVs) in EMT and their contributions to CRSwNP has not been extensively investigated.

METHODS

SEVs were isolated from nasal mucosa through ultracentrifugation. MicroRNA sequencing and reverse-transcription quantitative polymerase chain reaction were employed to analyze the differential expression of microRNAs carried by sEVs. Human nasal epithelial cells (hNECs) were used to assess the EMT-inducing effect of sEVs/microRNAs. EMT-associated markers were detected by western blotting and immunofluorescence. Dual-luciferase reporter assay was performed to determine the target gene of miR-375-3p. MicroRNA mimic, lentiviral, and plasmid transduction were used for functional experiments.

RESULTS

In line with the greater EMT status in eosinophilic CRSwNP (ENP), sEVs derived from ENP (ENP-sEVs) could induce EMT in hNECs. MiR-375-3p was elevated in ENP-sEVs compared to that in control and nonENP. MiR-375- 3p carried by ENP-sEVs facilitated EMT by directly targeting KH domain containing RNA binding (QKI) at seed sequences of 913-919, 1025-1033, and 2438-2444 in 3'-untranslated region. Inhibition of QKI by miR-375-3p overexpression promoted EMT, which could be reversed by restoration of QKI. Furthermore, the abundance of miR-375-3p in sEVs was closely correlated with the clinical symptom score and disease severity.

CONCLUSIONS

MiR-375-3p-enriched sEVs facilitated EMT by suppressing QKI in hNECs. The association of miR-375-3p with disease severity underscores its potential as both a diagnostic marker and a therapeutic target for the innovative management of CRSwNP.

Analysis of the Correlation and Prognostic Significance of Tertiary Lymphoid Structures in Breast Cancer: A Radiomics-Clinical Integration Approach

BACKGROUND

Tertiary lymphoid structures (TLSs) are potential prognostic indicators. Radiomics may help reduce unnecessary invasive operations.

PURPOSE

To analyze the association between TLSs and prognosis, and to establish a nomogram model to evaluate the expression of TLSs in breast cancer (BC) patients.

STUDY TYPE

Retrospective.

POPULATION

Two hundred forty-two patients with localized primary BC (confirmed by surgery) were divided into BC + TLS group (N = 122) and BC - TLS group (N = 120).

FIELD STRENGTH/SEQUENCE

3.0T; Caipirinha-Dixon-TWIST-volume interpolated breath-hold sequence for dynamic contrast-enhanced (DCE) MRI and inversion-recovery turbo spin echo sequence for T2-weighted imaging (T2WI).

ASSESSMENT

Three models for differentiating BC + TLS and BC - TLS were developed: 1) a clinical model, 2) a radiomics signature model, and 3) a combined clinical and radiomics (nomogram) model. The overall survival (OS), distant metastasis-free survival (DMFS), and disease-free survival (DFS) were compared to evaluate the prognostic value of TLSs.

STATISTICAL TESTS

LASSO algorithm and ANOVA were used to select highly correlated features. Clinical relevant variables were identified by multivariable logistic regression. Model performance was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC), and through decision curve analysis (DCA). The Kaplan-Meier method was used to calculate the survival rate.

RESULTS

The radiomics signature model (training: AUC 0.766; test: AUC 0.749) and the nomogram model (training: AUC 0.820; test: AUC 0.749) showed better validation performance than the clinical model. DCA showed that the nomogram model had a higher net benefit than the other models. The median follow-up time was 52 months. While there was no significant difference in 3-year OS (P = 0.22) between BC + TLS and BC - TLS patients, there were significant differences in 3-year DFS and 3-year DMFS between the two groups.

DATA CONCLUSION

The nomogram model performs well in distinguishing the presence or absence of TLS. BC + TLS patients had higher long-term disease control rates and better prognoses than those without TLS.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

The clinical applications of D-type parastomal hernia repair surgery

OBJECTIVE

This study investigated the use of a modified laparoscopic repair of paraostomy hernia technique, called "D-Type parastomal hernia repair surgery" which combines abdominal wall and extraperitoneal stoma reconstruction, in patients with parastomal hernia (PSH) following colorectal stoma surgery. The aim was to determine whether D-type parastomal hernia repair surgery is a promising surgical approach compared to the traditional laparoscopic repair technique (Sugarbaker method) for patients with PSH.

METHODS

PSH patients were selected and retrospectively divided into two groups: the study group underwent D-type parastomal hernia repair, while the control group underwent laparoscopic Sugarbaker repair. Clinical data from both groups were analyzed.

RESULT

Compared to control group (n = 68), the study group undergoing D-type stoma lateral hernia repair had significant increase in total operative time (98.82 ± 12.37 min vs 124.61 ± 34.99 min, p < 0.001). The study group also showed better postoperative stoma bowel function scores in sensory ability, frequency of bowel movements, and clothing cleanliness without a stoma bag (p = 0.037, 0.001, 0.002). The treatment cost was significantly higher in the control group (3899.97 ± 260.00$ vs 3215.91 ± 230.03$, p < 0.001). The postoperative recurrence rate in the control group was 26.4%, while in the study group, it was 4.3%, with a significant statistical difference (p = 0.024). In terms of long-term postoperative complications, the study group had an overall lower incidence compared to the control group (p = 0.035). Other parameters showed no significant differences between the two groups.

CONCLUSION

The study suggests that D-type parastomal hernia repair surgery is a safe and feasible procedure. Compared to traditional surgery, it can reduce the recurrence of lateral hernia, improve postoperative stoma bowel function, and save medical resources.

A revisit of drugs and potential therapeutic targets against non-alcoholic fatty liver disease: learning from clinical trials

PURPOSE

Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease, with a worldwide prevalence of 25%. Although numerous clinical trials have been conducted over the last few decades, an effective treatment has not been approved yet. Extensive research has accumulated a large amount of data and experience; however, the vast number of clinical trials and new therapeutic targets for NAFLD make it impossible to keep abreast of the relevant information. Therefore, a systematic analysis of the existing trials is necessary.

METHODS

Here, we reviewed clinical trials on NAFLD registered in the mandated federal database, ClinicalTrials.gov, to generate a detailed overview of the trials related to drugs and therapeutic targets for NAFLD treatment. Following screening for pertinence to therapy, a total of 440 entries were identified that included active trials as well as those that have already been completed, suspended, terminated, or withdrawn.

RESULTS

We summarize and systematically analyze the state, drug development pipeline, and discovery of treatment targets for NAFLD. We consider possible factors that may affect clinical outcomes. Furthermore, we discussed these results to explore the mechanisms responsible for clinical outcomes.

CONCLUSION

We summarised the landscape of current clinical trials and suggested the directions for future NAFLD therapy to assist internal medicine specialists in treating the whole clinical spectrum of this highly prevalent liver disease.

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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Measurements of All-Particle Energy Spectrum and Mean Logarithmic Mass of Cosmic Rays from 0.3 to 30 PeV with LHAASO-KM2A

We present the measurements of all-particle energy spectrum and mean logarithmic mass of cosmic rays in the energy range of 0.3-30 PeV using data collected from LHAASO-KM2A between September 2021 and December 2022, which is based on a nearly composition-independent energy reconstruction method, achieving unprecedented accuracy. Our analysis reveals the position of the knee at 3.67±0.05±0.15  PeV. Below the knee, the spectral index is found to be -2.7413±0.0004±0.0050, while above the knee, it is -3.128±0.005±0.027, with the sharpness of the transition measured with a statistical error of 2%. The mean logarithmic mass of cosmic rays is almost heavier than helium in the whole measured energy range. It decreases from 1.7 at 0.3 PeV to 1.3 at 3 PeV, representing a 24% decline following a power law with an index of -0.1200±0.0003±0.0341. This is equivalent to an increase in abundance of light components. Above the knee, the mean logarithmic mass exhibits a power law trend towards heavier components, which is reversal to the behavior observed in the all-particle energy spectrum. Additionally, the knee position and the change in power-law index are approximately the same. These findings suggest that the knee observed in the all-particle spectrum corresponds to the knee of the light component, rather than the medium-heavy components.

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.

High-throughput DNA synthesis for data storage

With the explosion of digital world, the dramatically increasing data volume is expected to reach 175 ZB (1 ZB = 1012 GB) in 2025. Storing such huge global data would consume tons of resources. Fortunately, it has been found that the deoxyribonucleic acid (DNA) molecule is the most compact and durable information storage medium in the world so far. Its high coding density and long-term preservation properties make itself one of the best data storage carriers for the future. High-throughput DNA synthesis is a key technology for "DNA data storage", which encodes binary data stream (0/1) into quaternary long DNA sequences consisting of four bases (A/G/C/T). In this review, the workflow of DNA data storage and the basic methods of artificial DNA synthesis technology are outlined first. Then, the technical characteristics of different synthesis methods and the state-of-the-art of representative commercial companies, with a primary focus on silicon chip microarray-based synthesis and novel enzymatic DNA synthesis are presented. Finally, the recent status of DNA storage and new opportunities for future development in the field of high-throughput, large-scale DNA synthesis technology are summarized.

Highly Sensitive Iontronic Pressure Sensor with Side-by-Side Package Based on Alveoli and Arch Structure

Flexible pressure sensors play a significant role in wearable devices and electronic skin. Iontronic pressure sensors with high sensitivity, wide measurement range, and high resolution can meet requirements. Based on the significant deformation characteristics of alveoli to improve compressibility, and the ability of the arch to disperse vertical pressure into horizontal thrust to increase contact area, a graded hollow ball arch (GHBA) microstructure is proposed, greatly improving sensitivity. The fabrication of GHBA ingeniously employs a double-sided structure. One side uses mold casting to create convex structures, while the other utilizes the evaporation of moisture during the curing process to form concave structures. At the same time, a novel side-by-side package structure is proposed, ensuring pressure on flexible substrate is maximally transferred to the GHBA microstructure. Within the range of 0.2 Pa-300 kPa, the iontronic pressure sensor achieves a maximum sensitivity of 10 420.8 kPa-1 , pressure resolution of 0.1% under the pressure of 100 kPa, and rapid response/recovery time of 40/35 ms. In wearable devices, it is capable of monitoring dumbbell curl exercises and wirelessly correcting sitting positions. In electronic skin, it can non-contactly detect the location of the wind source and achieve object classification prediction when combined with the CNN model.

Clinical and cardiac MRI characteristics: prognosis in patients with alcoholic cardiomyopathy

AIMS

Alcoholic cardiomyopathy (ACM) is recognized as a type of non-ischemic dilated cardiomyopathy (DCM). To date, the clinical prognosis of ACM remains a topic of debate in previous studies and there are limited studies on its cardiac MRI characteristics. The aim of this study was to summarize the clinical and MRI features of ACM patients and to identify the predictors of adverse prognosis based on clinical characteristics and MRI imaging findings.

MATERIALS AND METHODS

Adult patients who were clinically diagnosed with ACM and underwent enhanced CMR between September 2015 and August 2022 were retrospectively enrolled. The primary endpoints were major adverse cardiovascular events, including cardiac-related death, heart transplantation, hospitalization for heart failure and life-threatening ventricular arrhythmias (sustained ventricular tachycardia, ventricular fibrillation, or ICD shock). The risk factors associated with these primary end points were identified using multivariable Cox analysis.

RESULTS

A total of 62 ACM patients (50 ± 9 years, 62 men) were included. The majority of patients presented with symptoms of heart failure. Over a median follow-up period of 30.3 months (IQR 12.2-57.7 months), 24 patients reached the primary endpoints. For clinical variables, multivariable analysis showed that drinking duration (HR=1.05; 95%CI:1.01, 1.11; p=0.03) and persistent drinking (HR=3.71; 95%CI:1.46, 9.44; p=0.01) were associated with MACE. For CMR variables, late gadolinium enhancement (LGE) percent (HR = 1.09; 95% CI: 1.03, 1.14; p<0.001) stood out as an independent predictor for MACE.

CONCLUSIONS

In ACM patients, persistent drinking and cardiac MRI-defined myocardial scar were associated with adverse outcomes such as cardiac death, heart transplantation, hospitalization for heart failure or life-threatening ventricular arrhythmias.

Surfactant-like Additives Assisted the Lateral Growth of Pentacene Films

Lateral growth of thin films is crucial for organic electronic devices, such as field-effect transistors. Here, we report a strategy to improve the lateral growth of pentacene films using rubrene as a surfactant-like additive. Atomic force microscopy (AFM) images confirm the enhanced lateral growth with the presence of rubrene, resulting in smooth and enlarged molecule domains in the films in comparison to those without rubrene. Molecular dynamics simulations are conducted to explore the interlayer diffusion of pentacene molecules during the growth. With the rubrene molecules as surfactant-like additives, mean square displacement (MSD) analysis shows that the pentacene molecules have a descending diffusion coefficient of 2.0 × 10-5 cm2 s-1, which is greater than the ascending diffusion coefficient of 1.6 × 10-5 cm2 s-1. The more descending molecules lead to an enhanced lateral growth of pentacene films, which is in good agreement with the experiments. As a result, the pentacene films grown with rubrene exhibit a rapid increase in carrier mobility over thickness due to the well-connected domains resulting from enhanced lateral growth. This finding will provide a new strategy to modulate the morphology of organic films for high-performance devices.

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}.

A 3D-printed microhemispherical shell resonator with electrostatic tuning for a Coriolis vibratory gyroscope

The emergence of microhemispherical resonant gyroscopes, which integrate the advantages of exceptional stability and long lifetime with miniaturization, has afforded new possibilities for the development of whole-angle gyroscopes. However, existing methods used for manufacturing microhemispherical resonant gyroscopes based on MEMS technology face the primary drawback of intricate and costly processing. Here, we report the design, fabrication, and characterization of the first 3D-printable microhemispherical shell resonator for a Coriolis vibrating gyroscope. We remarkably achieve fabrication in just two steps bypassing the dozen or so steps required in traditional micromachining. By utilizing the intricate shaping capability and ultrahigh precision offered by projection microstereolithography, we fabricate 3D high-aspect-ratio resonant structures and controllable capacitive air gaps, both of which are extremely difficult to obtain via MEMS technology. In addition, the resonance frequency of the fabricated resonators can be tuned by electrostatic forces, and the fabricated resonators exhibit a higher quality factor in air than do typical MEMS microhemispherical resonators. This work demonstrates the feasibility of rapidly batch-manufacturing microhemispherical shell resonators, paving the way for the development of microhemispherical resonator gyroscopes for portable inertial navigation. Moreover, this particular design concept could be further applied to increase uptake of resonator tools in the MEMS community.

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

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

Glymphatic system dysfunction in middle-aged and elderly chronic insomnia patients with cognitive impairment evidenced by diffusion tensor imaging along the perivascular space (DTI-ALPS)

BACKGROUND

Chronic insomnia impairs the glymphatic system and may lead to cognitive impairment and dementia in elderly population. The diffusion tensor image analysis along the perivascular space (DTI-ALPS) has been proposed as a non-invasive method to measure the activity of human brain glymphatic. We aim to explore whether glymphatic function is impaired in middle-aged and elderly chronic insomnia individuals and to identify the relationships between glymphatic dysfunction and cognitive impairment.

METHODS

A total of 33 chronic insomnia patients (57.36 ± 5.44 years, 30 females) and 20 age- and sex-matched healthy controls (57.95 ± 5.78 years, 16 females) were prospectively enrolled between May 2022 and January 2023. All participants completed MRI screening, cognition and sleep assessments, and DTI-ALPS index analysis.

RESULTS

Our findings revealed that the DTI-ALPS index was significantly difference among the chronic insomnia patients with impaired cognition group (1.32 ± 0.14), with normal cognition group (1.46 ± 0.09), and healthy controls (1.61 ± 0.16) (p = 0.0012, p < 0.0001, p = 0.0008, respectively). Mini-Mental State Examination (MMSE) scores of chronic insomnia patients with cognitive impairment were positively correlated with the DTI-ALPS index (Partial correlation analyses after correction for age, sex, education level and duration of chronic insomnia: r = 0.78, p = 0.002). DTI-ALPS had moderate accuracy in distinguishing chronic insomnia patients with cognitive impairment from those with normal cognition.

DATA CONCLUSION

The glymphatic system dysfunction is involved in chronic insomnia among middle-aged and elderly individuals, and it has been found to be correlated with cognitive decline.

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.

Maternal androgen excess inhibits fetal cardiomyocytes proliferation through RB-mediated cell cycle arrest and induces cardiac hypertrophy in adulthood

PURPOSE

Maternal hyperandrogenism during pregnancy is associated with adverse gestational outcomes and chronic non-communicable diseases in offspring. However, few studies are reported to demonstrate the association between maternal androgen excess and cardiac health in offspring. This study aimed to explore the relation between androgen exposure in utero and cardiac health of offspring in fetal and adult period. Its underlying mechanism is also illustrated in this research.

METHODS

Pregnant mice were injected with dihydrotestosterone (DHT) from gestational day (GD) 16.5 to GD18.5. On GD18.5, fetal heart tissue was collected for metabolite and morphological analysis. The hearts from adult offspring were also collected for morphological and qPCR analysis. H9c2 cells were treated with 75 μM androsterone. Immunofluorescence, flow cytometry, qPCR, and western blot were performed to observe cell proliferation and explore the underlying mechanism.

RESULTS

Intrauterine exposure to excessive androgen led to thinner ventricular wall, decreased number of cardiomyocytes in fetal offspring and caused cardiac hypertrophy, compromised cardiac function in adult offspring. The analysis of steroid hormone metabolites in fetal heart tissue by ultra performance liquid chromatography and tandem mass spectrometry showed that the content of androgen metabolite androsterone was significantly increased. Mechanistically, H9c2 cells treated with androsterone led to a significant decrease in phosphorylated retinoblastoma protein (pRB) and cell cycle-related protein including cyclin-dependent kinase 2 (CDK2), cyclin-dependent kinase 4 (CDK4), and cyclin D1 (CCND1) in cardiomyocytes. This resulted in cell cycle arrest at G1-S phase, which in turn inhibited cardiomyocyte proliferation.

CONCLUSION

Taken together, our results indicate that in utero exposure to DHT, its metabolite androsterone could directly decrease cardiomyocytes proliferation through cell cycle arrest, which has a life-long-lasting effect on cardiac health. Our study highlights the importance of monitoring sex hormones in women during pregnancy and the follow-up of cardiac function in offspring with high risk of intrauterine androgen exposure.

Comparison of the properties of phenolic resin synthesized from different aldehydes and evaluation of the release and health risks of VOCs

Different amounts of glyoxal and paraformaldehyde were used to synthesize phenol-glyoxal (PG) and phenol-paraformaldehyde (PPF) resins, which were compared with conventional phenol-formaldehyde (PF) resins. Glyoxal oxidation leads to a pH value of 9.83 for PG 2.2. With the addition of polyformaldehyde, PPF 2.2 exhibited the highest viscosity at 17333.33 mPa s. The PPF 2.0 plywood has a maximum bonding strength of 1.94 MPa. The formaldehyde emission of PG 1.8 plywood is found to have a minimum value of 0.025 mg/m3, reaching the ENF limit (≤0.025 mg/m3). Acetaldehyde is found only in volatile organic compound (VOC) emissions from PG plywood and is associated with increased glyoxal. PPF plywood emitted more aromatic and total VOC (TVOC) than the other two plywood types. The measured TVOC for PPF 2.2 is 196.07 μg/m3. The results showed that the total cancer risk (TCR) values of PPF 1.8, PPF 2.0, and PG 1.8 were above the threshold of 1.00E-4, indicating a definite carcinogenic risk. Acetaldehyde in the PG plywood exceeded the safety threshold for noncarcinogenic risk. The use of paraformaldehyde in the wood-based panel production is been considered a possible means of improving the bonding strength of plywood. Glyoxal has also been shown to be a viable method for lowering the formaldehyde emissions from plywood. The VOC emissions from plywood changed significantly depending on the aldehyde used. Limiting VOCs that present high health hazards is crucial for reducing the negative impact of plywood on both indoor environments and human health.

Genetic basis of maize stalk strength decoded via linkage and association mapping

Stalk lodging is a severe problem that limits maize production worldwide, although little attention has been given to its genetic basis. Here we measured rind penetrometer resistance (RPR), an effective index for stalk lodging, in a multi-parent population of 1948 recombinant inbred lines (RILs) and an association population of 508 inbred lines (AMP508). Linkage and association mapping identified 53 and 29 single quantitative trait loci (QTLs) and 50 and 19 pairs of epistatic interactions for RPR in the multi-parent population and AMP508 population, respectively. Phenotypic variation explained by all identified epistatic QTLs (up to ~5%) was much less than that explained by all single additive QTLs (up to ~33% in the multi-parent population and ~ 60% in the AMP508 population). Among all detected QTLs, only eight single QTLs explained >10% of phenotypic variation in single RIL populations. Alleles that increased RPR were enriched in tropical/subtropical (TST) groups from the AMP508 population. Based on genome-wide association studies in both populations, we identified 137 candidate genes affecting RPR, which were assigned to multiple biological processes, such as the biosynthesis of cell wall components. Sixty-six candidate genes were cross-validated by multiple methods or populations. Most importantly, 23 candidate genes were upregulated or downregulated in high-RPR lines relative to low-RPR lines, supporting the associations between candidate genes and RPR. These findings reveal the complex nature of the genetic basis underlying RPR and provide loci or candidate genes for developing elite varieties that are resistant to stalk lodging via molecular breeding.

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.

An Automated Heart Shunt Recognition Pipeline Using Deep Neural Networks

Automated recognition of heart shunts using saline contrast transthoracic echocardiography (SC-TTE) has the potential to transform clinical practice, enabling non-experts to assess heart shunt lesions. This study aims to develop a fully automated and scalable analysis pipeline for distinguishing heart shunts, utilizing a deep neural network-based framework. The pipeline consists of three steps: (1) chamber segmentation, (2) ultrasound microbubble localization, and (3) disease classification model establishment. The study's normal control group included 91 patients with intracardiac shunts, 61 patients with extracardiac shunts, and 84 asymptomatic individuals. Participants' SC-TTE images were segmented using the U-Net model to obtain cardiac chambers. The segmentation results were combined with ultrasound microbubble localization to generate multivariate time series data on microbubble counts in each chamber. A classification model was then trained using this data to distinguish between intracardiac and extracardiac shunts. The proposed framework accurately segmented heart chambers (dice coefficient = 0.92 ± 0.1) and localized microbubbles. The disease classification model achieved high accuracy, sensitivity, specificity, F1 score, kappa value, and AUC value for both intracardiac and extracardiac shunts. For intracardiac shunts, accuracy was 0.875 ± 0.008, sensitivity was 0.891 ± 0.002, specificity was 0.865 ± 0.012, F1 score was 0.836 ± 0.011, kappa value was 0.735 ± 0.017, and AUC value was 0.942 ± 0.014. For extracardiac shunts, accuracy was 0.902 ± 0.007, sensitivity was 0.763 ± 0.014, specificity was 0.966 ± 0.008, F1 score was 0.830 ± 0.012, kappa value was 0.762 ± 0.017, and AUC value was 0.916 ± 0.006. The proposed framework utilizing deep neural networks offers a fast, convenient, and accurate method for identifying intracardiac and extracardiac shunts. It aids in shunt recognition and generates valuable quantitative indices, assisting clinicians in diagnosing these conditions.

A tumor suppressor protein encoded by circKEAP1 inhibits osteosarcoma cell stemness and metastasis by promoting vimentin proteasome degradation and activating anti-tumor immunity

BACKGROUND

Osteosarcoma (OS) is one of most commonly diagnosed bone cancer. Circular RNAs (circRNAs) are a class of highly stable non-coding RNA, the majority of which have not been characterized functionally. The underlying function and molecular mechanisms of circRNAs in OS have not been fully demonstrated.

METHOD

Microarray analysis was performed to identify circRNAs that are differentially-expressed between OS and corresponding normal tissues. The biological function of circKEAP1 was confirmed in vitro and in vivo. Mass spectrometry and western blot assays were used to identify the circKEAP1-encoded protein KEAP1-259aa. The molecular mechanism of circKEAP1 was investigated by RNA sequencing and RNA immunoprecipitation analyses.

RESULTS

Here, we identified a tumor suppressor circKEAP1, originating from the back-splicing of exon2 of the KEAP1 gene. Clinically, circKEAP1 is downregulated in OS tumors and associated with better survival in cancer patients. N6-methyladenosine (m6A) at a specific adenosine leads to low expression of circKEAP1. Further analysis revealed that circKEAP1 contained a 777 nt long ORF and encoded a truncated protein KEAP1-259aa that reduces cell proliferation, invasion and tumorsphere formation of OS cells. Mechanistically, KEAP1-259aa bound to vimentin in the cytoplasm to promote vimentin proteasome degradation by interacting with the E3 ligase ARIH1. Moreover, circKEAP1 interacted with RIG-I to activate anti-tumor immunity via the IFN-γ pathway.

CONCLUSION

Taken together, our findings characterize a tumor suppressor circKEAP1 as a key tumor suppressor regulating of OS cell stemness, proliferation and migration, providing potential therapeutic targets for treatment of OS.

[Hemodynamic changes with serial balloon pulmonary angioplasty in chronic thromboembolic pulmonary hypertension]

Objective: To monitor hemodynamic changes during serial balloon pulmonary angioplasty (BPA) for chronic thromboembolic pulmonary hypertension (CTEPH). Methods: General clinical data of CTEPH patients diagnosed from October 2017 to January 2022 in Beijing Chaoyang Hospital were collected, and 83 patients who underwent at least 1 BPA treatment were included to analyze their 6 min walking distance, WHO functional class, N-terminal B-type natriuretic peptide precursor (NT-proBNP), troponin I (cTnI) and haemodynamic indices. Baseline and follow-up after the final BPA clinical data and hemodynamics, functional status and serial hemodynamics before each series of BPA were collected to evaluate the efficacy of BPA for CTEPH patients. Complications and managements were documented to confirm the safety of BPA for CTEPH patients. Results: Three hundred and forty BPA procedures were performed in 83 CTEPH patients. The median number of BPA procedures was 4.0 and a total of 2104 vessels were dilated. In general, mPAP [from 50.0(42.0-55.25) mmHg(1 mmHg=0.133 kPa) to 32.0(27.0-42.0) mmHg, P<0.001], PVR[from (806.6±323.2) dyn·s·cm-5 to 420.0(295.0-613.5) dyn·s·cm-5, P<0.001] were significantly improved compared with baseline, but not CO and CI. Functional parameters including WHO functional class Ⅰ/Ⅱ/Ⅲ/Ⅳ (from 0/35/34/14 to 43/32/7/1, P<0.001), 6MWD [from 364.5(300.0-429.5)m to 461.0(409.0-501.0)m, P<0.001], NT-proBNP [from 1 357.0(232.0-2 715.0) ng/L to 141.0(57.0-627.8) ng/L,P<0.001] were significantly improved compared with baseline. A cumulative (compared to baseline) and serial (compared to preceding BPA session) analysis of the sequential BPA session confirmed that a major hemodynamic improvement in PVR and mPAP occurred in the first 3 serial BPA treatments. There was a dose-response relationship: the more segments that were treated, the greater were the subsequent reduction in PVR and mPAP. There were 32.0 complications (9.4%) associated with BPA procedures, and the most common complication was pulmonary hemorrhage caused by catheter-related vascular injury. Conclusions: BPA is an effective and safe alternative for technically non-operable CTEPH patients. The hemodynamic benefits of BPA in CTEPH patients were cumulative and correlated with the total number of vessels successfully dilated.

[Research on the framework of biosafety standards for pathogenic microbial laboratories]

Developing and implementing biosafety standards for pathogenic microbiology laboratories is essential to achieving scientific, efficient, and standardized management and operation. This article analyzes the current standardization construction in biosafety in pathogenic microbiology laboratories domestically and internationally. It proposes a framework for the biosafety standard system of pathogenic microbiology laboratories, which mainly includes four parts: basic standards, management standards, technical standards, and industry applications. It provides a reference for the standardization work of pathogenic microbiology laboratories and helps to standardize the biosafety industry in China.

[The effect of Ba Duan Jin on the balance of community-dwelling older adults: a cluster randomized control trial]

Objective: To assess the effectiveness of a 6-month Ba Duan Jin exercise program in improving the balance of community-dwelling older adults. Methods: A two arms, parallel-group, cluster randomized controlled trial was conducted in 1 028 community residents aged 60-80 years in 40 communities in 5 provinces of China. Participants in the intervention group (20 communities, 523 people) received Ba Duan Jin exercise 5 days/week, 1 hour/day for 6 months, and three times of falls prevention health education, and the control group (20 communities, 505 people) received falls prevention health education same as the intervention group. The Berg balance scale (BBS) score was the leading outcome indicator, and the secondary outcome indicators included the length of time of standing on one foot (with eyes open and closed), standing in a tandem stance (with eyes open and closed), the closed circle test, and the timed up to test. Results: A total of 1 028 participants were included in the final analysis, including 731 women (71.11%) and 297 men (28.89%), and the age was (69.87±5.67) years. After the 3-month intervention, compared with the baseline data, the BBS score of the intervention group was significantly higher than the control group by 3.05 (95%CI: 2.23-3.88) points (P<0.001). After the 6-month intervention, compared with the baseline data, the BBS score of the intervention group was significantly higher than the control group by 4.70 (95%CI: 4.03-5.37) points (P<0.001). Ba Duan Jin showed significant improvement (P<0.05) in all secondary outcomes after 6 months of exercise in the intervention group compared with the control group. Conclusions: This study showed that Ba Duan Jin exercise can improve balance in community-dwelling older adults aged 60-80. The longer the exercise time, the better the improvement.

Duplex-Hierarchy Representation Learning for Remote Sensing Image Classification

Remote sensing image classification (RSIC) is designed to assign specific semantic labels to aerial images, which is significant and fundamental in many applications. In recent years, substantial work has been conducted on RSIC with the help of deep learning models. Even though these models have greatly enhanced the performance of RSIC, the issues of diversity in the same class and similarity between different classes in remote sensing images remain huge challenges for RSIC. To solve these problems, a duplex-hierarchy representation learning (DHRL) method is proposed. The proposed DHRL method aims to explore duplex-hierarchy spaces, including a common space and a label space, to learn discriminative representations for RSIC. The proposed DHRL method consists of three main steps: First, paired images are fed to a pretrained ResNet network for extracting the corresponding features. Second, the extracted features are further explored and mapped into a common space for reducing the intra-class scatter and enlarging the inter-class separation. Third, the obtained representations are used to predict the categories of the input images, and the discrimination loss in the label space is minimized to further promote the learning of discriminative representations. Meanwhile, a confusion score is computed and added to the classification loss for guiding the discriminative representation learning via backpropagation. The comprehensive experimental results show that the proposed method is superior to the existing state-of-the-art methods on two challenging remote sensing image scene datasets, demonstrating that the proposed method is significantly effective.

Indoor flow datasets of two-layered cross-ventilation models by particle image velocimetry and hot wire anemometry

This data article provides temporally and spatially high-resolution datasets of the indoor velocity fields for cross-ventilation models of two-layered simplified buildings separated by a second floor at the middle height with an opening using wind-tunnel experiments. The datasets are based on the research article entitled "Quantifying natural cross-ventilation flow of a two-layered model used for terraced houses in tropical zones by particle image velocimetry" by Ali et al. [1]. Two cases are considered based on the positions of the inlet and outlet openings on each floor. The measurements were conducted using hot-wire anemometry (HWA) with 10,000 Hz and particle image velocimetry (PIV) with 1000 Hz for a sufficiently long period to determine reliable statistics of the mean, variances, and covariances. In addition, the article provides the instantaneous datasets of two velocity components determined by PIV for the cross-ventilation models. The datasets can be used for both computational fluid dynamics (CFD) validation and further investigation of turbulent flow nature of the multi-layer cross ventilation flow.

Tdrd3-null mice show post-transcriptional and behavioral impairments associated with neurogenesis and synaptic plasticity

The Topoisomerase 3B (Top3b) - Tudor domain containing 3 (Tdrd3) protein complex is the only dual-activity topoisomerase complex that can alter both DNA and RNA topology in animals. TOP3B mutations in humans are associated with schizophrenia, autism and cognitive disorders; and Top3b-null mice exhibit several phenotypes observed in animal models of psychiatric and cognitive disorders, including impaired cognitive and emotional behaviors, aberrant neurogenesis and synaptic plasticity, and transcriptional defects. Similarly, human TDRD3 genomic variants have been associated with schizophrenia, verbal short-term memory and educational attainment. However, the importance of Tdrd3 in normal brain function has not been examined in animal models. Here we generated a Tdrd3-null mouse strain and demonstrate that these mice display both shared and unique defects when compared to Top3b-null mice. Shared defects were observed in cognitive behaviors, synaptic plasticity, adult neurogenesis, newborn neuron morphology, and neuronal activity-dependent transcription; whereas defects unique to Tdrd3-deficient mice include hyperactivity, changes in anxiety-like behaviors, olfaction, increased new neuron complexity, and reduced myelination. Interestingly, multiple genes critical for neurodevelopment and cognitive function exhibit reduced levels in mature but not nascent transcripts. We infer that the entire Top3b-Tdrd3 complex is essential for normal brain function, and that defective post-transcriptional regulation could contribute to cognitive and psychiatric disorders.

[To investigate the role of the AAC-8 scoring in predicting restenosis or occlusion of lower extremity arteries after dilatation and angioplasty with DCB]

Objective: To investigate the role of the Abdominal Aortic Calcification-8 (AAC-8) scoring system in predicting restenosis or occlusion of lower extremity arteries after dilatation and angioplasty with drug-coated balloon (DCB). Methods: In this retrospective study, 62 patients who underwent dilatation and angioplasty with DCB for lower limb atherosclerotic obliterans (ASO) were enrolled from September 2018 to June 2022 in Nanjing Drum Tower Hospital Affiliated to Nanjing University Medical School. Among them who aged (73.9±11.3) years, 37 were males and 25 were females. Patients were divided into two groups according to the condition of the lower extremity arteries after dilatation and angioplasty with DCB: recurrence group (n=26) and patency group (n=36). Logistic regression was used to analyze the factors associated with restenosis or occlusion of lower extremity arteries after dilatation and angioplasty with DCB. The predictive value of the AAC-8 score for restenosis or occlusion of the lower extremity arteries after dilatation and angioplasty with DCB was analyzed using the receiver operating characteristic curves (ROC curves). Results: The postoperative follow-up was 16.30 (10.97, 24.10) months in the patency group and 9.03 (6.98, 15.31) months in the recurrence group. The results of multifactorial logistic regression analysis showed that an elevated AAC-8 score (OR=1.388, 95%CI: 1.067-1.806, P=0.015) was an associated factor of restenosis or occlusion of the lower extremity arteries after dilatation and angioplasty with DCB. The ROC curve analysis showed that the area under the curve (AUC) of the AAC-8 score for predicting restenosis or occlusion of the lower extremity arteries after dilatation and angioplasty with DCB was 0.687 (95%CI: 0.550-0.824, P=0.013), with a cut-off value of 5.5 points, a sensitivity of 65.4% and a specificity of 69.5%. Conclusions: Elevated AAC-8 score is associated with restenosis or occlusion of the lower extremity arteries after dilatation and angioplasty with DCB. When the cut-off value is 5.5, the AAC-8 score predicts restenosis or occlusion of the lower extremity arteries after DCB dilation and angioplasty with a sensitivity of 65.4% and a specificity of 69.5%.

RNA-binding protein Nocte regulates Drosophila development by promoting translation reinitiation on mRNAs with long upstream open reading frames

RNA-binding proteins (RBPs) with intrinsically disordered regions (IDRs) are linked to multiple human disorders, but their mechanisms of action remain unclear. Here, we report that one such protein, Nocte, is essential for Drosophila eye development by regulating a critical gene expression cascade at translational level. Knockout of nocte in flies leads to lethality, and its eye-specific depletion impairs eye size and morphology. Nocte preferentially enhances translation of mRNAs with long upstream open reading frames (uORFs). One of the key Nocte targets, glass mRNA, encodes a transcription factor critical for differentiation of photoreceptor neurons and accessory cells, and re-expression of Glass largely rescued the eye defects caused by Nocte depletion. Mechanistically, Nocte counteracts long uORF-mediated translational suppression by promoting translation reinitiation downstream of the uORF. Nocte interacts with translation factors eIF3 and Rack1 through its BAT2 domain, and a Nocte mutant lacking this domain fails to promote translation of glass mRNA. Notably, de novo mutations of human orthologs of Nocte have been detected in schizophrenia patients. Our data suggest that Nocte family of proteins can promote translation reinitiation to overcome long uORFs-mediated translational suppression, and disruption of this function can lead to developmental defects and neurological disorders.

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

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

Observation of WZγ Production in pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector

This Letter reports the observation of WZγ production and a measurement of its cross section using 140.1±1.2  fb^{-1} of proton-proton collision data recorded at a center-of-mass energy of 13 TeV by the ATLAS detector at the Large Hadron Collider. The WZγ production cross section, with both the W and Z bosons decaying leptonically, pp→WZγ→ℓ^{'}^{±}νℓ^{+}ℓ^{-}γ (ℓ^{(^{'})}=e, μ), is measured in a fiducial phase-space region defined such that the leptons and the photon have high transverse momentum and the photon is isolated. The cross section is found to be 2.01±0.30(stat)±0.16(syst)  fb. The corresponding standard model predicted cross section calculated at next-to-leading order in perturbative quantum chromodynamics and at leading order in the electroweak coupling constant is 1.50±0.06  fb. The observed significance of the WZγ signal is 6.3σ, compared with an expected significance of 5.0σ.

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

BACKGROUND

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

METHODS

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

FINDINGS

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

INTERPRETATION

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

FUNDING

Boehringer Ingelheim and Eli Lilly.

Factors associated with nocturnal and diurnal glycemic variability in patients with type 2 diabetes: a cross-sectional study

PURPOSE

There is little information on factors that influence the glycemic variability (GV) during the nocturnal and diurnal periods. We aimed to examine the relationship between clinical factors and GV during these two periods.

METHODS

This cross-sectional study included 134 patients with type 2 diabetes. 24-h changes in blood glucose were recorded by a continuous glucose monitoring system. Nocturnal and diurnal GV were assessed by standard deviation of blood glucose (SDBG), coefficient of variation (CV), and mean amplitude of glycemic excursions (MAGE), respectively. Robust regression analyses were performed to identify the factors associated with GV. Restricted cubic splines were used to determine dose-response relationship.

RESULTS

During the nocturnal period, age and glycemic level at 12:00 A.M. were positively associated with GV, whereas alanine aminotransferase was negatively associated with GV. During the diurnal period, homeostatic model assessment 2-insulin sensitivity (HOMA2-S) was positively associated with GV, whereas insulin secretion-sensitivity index-2 (ISSI2) was negatively associated with GV. Additionally, we found a J-shape association between the glycemic level at 12:00 A.M. and MAGE, with 9.0 mmol/L blood glucose level as a cutoff point. Similar nonlinear associations were found between ISSI2 and SDBG, and between ISSI2 and MAGE, with ISSI2 value of 175 as a cutoff point.

CONCLUSION

Factors associated with GV were different between nocturnal and diurnal periods. The cutoff points we found in this study may provide the therapeutic targets for beta-cell function and pre-sleep glycemic level in clinical practice.

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

BACKGROUND

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

METHODS

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

FINDINGS

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

INTERPRETATION

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

FUNDING

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

Combined Measurement of the Higgs Boson Mass from the H→γγ and H→ZZ^{*}→4ℓ Decay Channels with the ATLAS Detector Using sqrt[s]=7, 8, and 13 TeV pp Collision Data

A measurement of the mass of the Higgs boson combining the H→ZZ^{*}→4ℓ and H→γγ decay channels is presented. The result is based on 140  fb^{-1} of proton-proton collision data collected by the ATLAS detector during LHC run 2 at a center-of-mass energy of 13 TeV combined with the run 1 ATLAS mass measurement, performed at center-of-mass energies of 7 and 8 TeV, yielding a Higgs boson mass of 125.11±0.09(stat)±0.06(syst)=125.11±0.11  GeV. This corresponds to a 0.09% precision achieved on this fundamental parameter of the Standard Model of particle physics.

Search for Dark Photons in Rare Z Boson Decays with the ATLAS Detector

A search for events with a dark photon produced in association with a dark Higgs boson via rare decays of the standard model Z boson is presented, using 139  fb^{-1} of sqrt[s]=13  TeV proton-proton collision data recorded by the ATLAS detector at the Large Hadron Collider. The dark boson decays into a pair of dark photons, and at least two of the three dark photons must each decay into a pair of electrons or muons, resulting in at least two same-flavor opposite-charge lepton pairs in the final state. The data are found to be consistent with the background prediction, and upper limits are set on the dark photon's coupling to the dark Higgs boson times the kinetic mixing between the standard model photon and the dark photon, α_{D}ϵ^{2}, in the dark photon mass range of [5, 40] GeV except for the ϒ mass window [8.8, 11.1] GeV. This search explores new parameter space not previously excluded by other experiments.

All-Optical GeV Electron Bunch Generation in a Laser-Plasma Accelerator via Truncated-Channel Injection

We describe a simple scheme, truncated-channel injection, to inject electrons directly into the wakefield driven by a high-intensity laser pulse guided in an all-optical plasma channel. We use this approach to generate dark-current-free 1.2 GeV, 4.5% relative energy spread electron bunches with 120 TW laser pulses guided in a 110 mm-long hydrodynamic optical-field-ionized plasma channel. Our experiments and particle-in-cell simulations show that high-quality electron bunches were only obtained when the drive pulse was closely aligned with the channel axis, and was focused close to the density down ramp formed at the channel entrance. Start-to-end simulations of the channel formation, and electron injection and acceleration show that increasing the channel length to 410 mm would yield 3.65 GeV bunches, with a slice energy spread ∼5×10^{-4}.

Valsartan Attenuated Homocysteine-Induced Impaired Autophagy and ER Stress in Human Umbilical Vein Endothelial Cells

Hyperhomocysteinemia is a risk factor for various cardiovascular diseases. However, the mechanism underlying homocysteine- (Hcy-) induced vascular injury remains unclear. The purpose of the present study was to examine a potential mechanism by which Hcy induced injury in human umbilical vascular endothelial cells (HUVEC). The protein abundance of autophagy-related markers was markedly decreased after Hcy treatment, which was associated with endoplasmic reticulum (ER) stress and apoptosis in HUVECs. Protein expression level of angiotensin II type 1 receptor (AT1 receptor) was dramatically increased in response to Hcy. Valsartan, an AT1 receptor blocker, improved autophagy and prevented ER stress and apoptosis in HUVECs treated with Hcy. Consistent with this, silence of AT1 receptor with siRNA decreased the protein abundance of ER stress markers, prevented apoptosis, and promoted autophagy in HUVECs. Inhibition or knockdown of AT1 receptor was shown to be associated with suppression of p-GSK3β/GSK3β-p-mTOR/mTOR signaling pathway. Additionally, inhibition of autophagy by 3-MA aggravated Hcy-induced apoptosis, while amelioration of ER stress by 4-PBA prevented Hcy-induced injury in HUVECs. Hcy-induced HUVEC injury was likely attributed to AT1 receptor activation, leading to impaired autophagy, ER stress, and apoptosis.