Vesical Imaging-Reporting and Data System (VI-RADS) as a grouping imaging biomarker combined with a decision-tree mode to preoperatively predict the pathological grade of bladder cancer

AIM

To investigate whether the Vesical Imaging-Reporting and Data System (VI-RADS) could be used to develop a new non-invasive preoperative grade-prediction system to partially predict high-grade bladder cancer (HG-BC).

MATERIALS AND METHODS

The present study enrolled 89 primary BC patients prospectively from March 2022 to June 2023. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of VI-RADS for predicting HG-BC and muscle-invasive bladder cancer (MIBC) in the entire group. In the low VI-RADS (≤2) group, the decision tree-based method was used to obtain significant predictors and construct the decision-tree model (DT model). The performance of the DT model and low VI-RADS scores for predicting HG-BC was determined using ROC, calibration, and decision curve analyses.

RESULTS

At a cut-off of ≥3, the specificity and positive predictive value of VI-RADS for predicting HG-BC in the entire group was 100%, and the area under the ROC curve (AUC) was 0.697. Among 65 patients with low VI-RADS scores, the DT model showed an AUC of 0.884 in predicting HG-BC compared to 0.506 for low VI-RADS scores. Calibration and decision curve analyses showed that the DT model performed better than the low VI-RADS scores.

CONCLUSION

Most VI-RADS scores ≥3 correspond to HG-BCs. VI-RADS could be used as a grouping imaging biomarker for a pathological grade-prediction procedure, which in combination with the DT model for low VI-RADS (≤2) populations, would provide a potential preoperative non-invasive method of predicting HG-BC.

Improving image quality of triple-low-protocol renal artery CT angiography with deep-learning image reconstruction: a comparative study with standard-dose single-energy and dual-energy CT with adaptive statistical iterative reconstruction

AIM

To investigate the improvement in image quality of triple-low-protocol (low radiation, low contrast medium dose, low injection speed) renal artery computed tomography (CT) angiography (RACTA) using deep-learning image reconstruction (DLIR), in comparison with standard-dose single- and dual-energy CT (DECT) using adaptive statistical iterative reconstruction-Veo (ASIR-V) algorithm.

MATERIALS AND METHODS

Ninety patients for RACTA were divided into different groups: standard-dose single-energy CT (S group) using ASIR-V at 60% strength (60%ASIR-V), DECT (DE group) with 60%ASIR-V including virtual monochromatic images at 40 keV (DE40 group) and 70 keV (DE70 group), and the triple-low protocol single-energy CT (L group) with DLIR at high level (DLIR-H). The effective dose (ED), contrast medium dose, injection speed, standard deviation (SD), signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of abdominal aorta (AA), and left/right renal artery (LRA, RRA), and subjective scores were compared among the different groups.

RESULTS

The L group significantly reduced ED by 37.6% and 31.2%, contrast medium dose by 33.9% and 30.5%, and injection speed by 30% and 30%, respectively, compared to the S and DE groups. The L group had the lowest SD values for all arteries compared to the other groups (p<0.001). The SNR of RRA and LRA in the L group, and the CNR of all arteries in the DE40 group had highest value compared to others (p<0.05). The L group had the best comprehensive score with good consistency (p<0.05).

CONCLUSIONS

The triple-low protocol RACTA with DLIR-H significantly reduces the ED, contrast medium doses, and injection speed, while providing good comprehensive image quality.

Value of long non-coding RNA HAS2-AS1 as a diagnostic and prognostic marker of glioma

BACKGROUND

Glioma presents high incidence and poor prognosis, and therefore more effective treatments are needed. Studies have confirmed that long non-coding RNAs (lncRNAs) basically regulate various human diseases including glioma. It has been theorized that HAS2-AS1 serves as an lncRNA to exert an oncogenic role in varying cancers. This study aimed to assess the value of lncRNA HAS2-AS1 as a diagnostic and prognostic marker for glioma.

METHODS

The miRNA expression data and clinical data of glioma were downloaded from the TCGA database for differential analysis and survival analysis. In addition, pathological specimens and specimens of adjacent normal tissue from 80 patients with glioma were used to observe the expression of HAS2-AS1. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic ability and prognostic value of HAS2-AS1 in glioma. Meanwhile, a Kaplan-Meier survival curve was plotted to evaluate the survival of glioma patients with different HAS2-AS1 expression levels.

RESULTS

HAS2-AS1 was significantly upregulated in glioma tissues compared with normal tissue. The survival curves showed that overexpression of HAS2-AS1 was associated with poor overall survival (OS) and progression-free survival (PFS). Several clinicopathological factors of glioma patients, including tumor size and WHO grade, were significantly correlated with HAS2-AS1 expression in tissues. The ROC curve showed an area under the curve (AUC) value of 0.863, indicating that HAS2-AS1 had good diagnostic value. The ROC curve for the predicted OS showed an AUC of 0.906, while the ROC curve for predicted PFS showed an AUC of 0.88. Both suggested that overexpression of HAS2-AS1 was associated with poor prognosis.

CONCLUSIONS

Normal tissues could be clearly distinguished from glioma tissues based on HAS2-AS1 expression. Moreover, overexpression of HAS2-AS1 indicated poor prognosis in glioma patients. Therefore, HAS2-AS1 could be used as a diagnostic and prognostic marker for glioma.

Sub-region based radiomics analysis for prediction of isocitrate dehydrogenase and telomerase reverse transcriptase promoter mutations in diffuse gliomas

AIM

To enhance the prediction of mutation status of isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase (TERT) promoter, which are crucial for glioma prognostication and therapeutic decision-making, via sub-regional radiomics analysis based on multiparametric magnetic resonance imaging (MRI).

MATERIALS AND METHODS

A retrospective study was conducted on 401 participants with adult-type diffuse gliomas. Employing the K-means algorithm, tumours were clustered into two to four subregions. Sub-regional radiomics features were extracted and selected using the Mann-Whitney U-test, Pearson correlation analysis, and least absolute shrinkage and selection operator, forming the basis for predictive models. The performance of model combinations of different sub-regional features and classifiers (including logistic regression, support vector machines, K-nearest neighbour, light gradient boosting machine, and multilayer perceptron) was evaluated using an external test set.

RESULTS

The models demonstrated high predictive performance, with area under the receiver operating characteristic curve (AUC) values ranging from 0.918 to 0.994 in the training set for IDH mutation prediction and from 0.758 to 0.939 for TERT promoter mutation prediction. In the external test sets, the two-cluster radiomics features and the logistic regression model yielded the highest prediction for IDH mutation, resulting in an AUC of 0.905. Additionally, the most effective predictive performance with an AUC of 0.803 was achieved using the four-cluster radiomics features and the support vector machine model, specifically for TERT promoter mutation prediction.

CONCLUSION

The present study underscores the potential of sub-regional radiomics analysis in predicting IDH and TERT promoter mutations in glioma patients. These models have the capacity to refine preoperative glioma diagnosis and contribute to personalised therapeutic interventions for patients.

Tongue-Coating Microbial and Metabolic Characteristics in Halitosis

Halitosis is a common oral condition, which leads to social embarrassment and affects quality of life. Cumulative evidence has suggested the association of tongue-coating microbiome with the development of intraoral halitosis. The dynamic variations of tongue-coating microbiota and metabolites in halitosis have not been fully elucidated. Therefore, the present study aimed to determine the tongue-coating microbial and metabolic characteristics in halitosis subjects without other oral diseases using metagenomics and metabolomics analysis. The participants underwent oral examination, halitosis assessment, and tongue-coating sample collection for the microbiome and metabolome analysis. It was found that the microbiota richness and diversity were significantly elevated in the halitosis group. Furthermore, species from Actinomyces, Prevotella, Veillonella, and Solobacterium were significantly more abundant in the halitosis group. However, the Rothia and Streptococcus species exhibited opposite tendencies. Eleven Kyoto Encyclopedia of Genes and Genomes pathways were significantly enriched in the halitosis tongue coatings, including cysteine and methionine metabolism. Functional genes related to sulfur, indole, skatole, and cadaverine metabolic processes (such as serA, metH, metK and dsrAB) were identified to be more abundant in the halitosis samples. The metabolome analysis revealed that indole-3-acetic, ornithine, and L-tryptophan were significantly elevated in the halitosis samples. Furthermore, it was observed that the values of volatile sulfur compounds and indole-3-acetic abundances were positively correlated. The multiomics analysis identified the metagenomic and metabolomic characteristics to differentiate halitosis from healthy individuals using the least absolute shrinkage and selection operator logistic regression and random forest classifier. A total of 19 species and 39 metabolites were identified as features in halitosis patients, which included indole-3-acetic acid, Bacillus altitudinis, Candidatus Saccharibacteria, and Actinomyces species. In conclusion, an evident shift in microbiome and metabolome characteristics was observed in the halitosis tongue coating, which may have a potential etiological significance and provide novel insights into the mechanism for halitosis.

Effects of family dignity interventions combined with standard palliative care on family adaptability, cohesion, and anticipatory grief in adult advanced cancer survivors and their family caregivers: A randomized controlled trial

Background

Family involvement and comfort are equally important in palliative care. Dignity undertook a new meaning and novel challenges as a result of restrictions on visits and companionship during the pandemic. Family-centered family dignity interventions have been shown to be effective in increasing patients' sense of dignity, increasing levels of hope, and reducing psychological distress; however, the effectiveness in enhancing family adaptability and intimacy in the survivor-caregiver binary and reducing expected grief have been inconclusive.

Objectives

The primary objective of this study was to assess the efficacy of family dignity interventions on family adaptability and cohesion. The secondary objective was to explore the effects of the interventions on anticipatory grief and psychological distress, and the lasting effect 1 month after the intervention.

Design

A single-blinded, two-arm parallel group, randomized controlled trial was conducted in China.

Settings

and methods: Ninety-eight dyads who met the inclusion criteria were randomly assigned to the family dignity intervention (n = 51) or standard palliative care group (n = 47) between June and August 2022. Study outcomes were measured at baseline, immediately post-intervention, and at the 1-month follow-up post-intervention evaluation. Data were analyzed using the Kolmogorov-Smirnov test, chi-square test, Fisher's exact test, independent sample t-test, Wilcoxon rank-sum test, and generalized estimation equations. The Intention-To-Treat analysis was performed for all available data.

Results

In comparison to the control group, significant improvements in family adaptability and cohesion and anticipatory grief over post-intervention and 1-month follow-up were demonstrated among the patients in the intervention group. The intervention group of caregivers had significant improvement in anticipatory grief at post-intervention and 1-month follow-up. The level of psychological distress was significantly lower in the intervention group than the control group (p < 0.05) at 1-month follow-up but the differences were not statistically significant at post-intervention. All outcomes showed clear differences from baseline after the intervention and at the 1-month follow-up evaluation but not between post-intervention and at the 1-month follow-up evaluation.

Conclusion

This study further verifies the actual effect of family dignity intervention program through randomized controlled trials, and provides a reference for improving the family relationship between advanced cancer patients and their family caregivers, and improving their mental health. The addition of family dignity intervention to standard palliative care greatly increased the adaptability and cohesion between survivors and their families, lessened the anticipatory grief of the survivor-caregiver pair, and relieved caregivers' anxiety and despair. We did not detect a statistically significant difference between post-intervention and the 1-month follow-up evaluation, suggesting that the intervention may have a durable impact at least 1 month.

Research progress of circadian rhythm in cardiovascular disease: A bibliometric study from 2002 to 2022

Background

Given that the circadian rhythm is intricately linked to cardiovascular physiological functions, the objective of this investigation was to employ bibliometric visualization analysis in order to scrutinize the trends, hotspots, and prospects of the circadian rhythm and cardiovascular disease (CVD) over the past two decades.

Methods

A thorough exploration of the literature related to the circadian rhythm and CVD was conducted via the Web of Science Core Collection database spanning the years 2002-2022. Advanced software tools, including citespace and VOSviewer, were employed to carry out a comprehensive analysis of the co-occurrence and collaborative relationships among countries, institutions, journals, references, and keywords found in this literature. Furthermore, correlation mapping was executed to provide a visual representation of the data.

Results

The present study encompassed a total of 3399 published works, comprising of 2691 articles and 708 reviews. The publications under scrutiny were primarily derived from countries such as the United States, Japan, and China. The most prominent research institutions were found to be the University of Vigo, University of Minnesota, and Harvard University. Notably, the journal Chronobiology International, alongside its co-cited publications, had the most substantial contribution to the research in this field. Following an exhaustive analysis, the most frequently observed keywords were identified as circadian rhythm, blood pressure, hypertension, heart rate, heart rate variability, and melatonin. Furthermore, a nascent analysis indicated that future research might gravitate towards topics such as inflammation, metabolism, oxidative stress, and autophagy, thereby indicating new directions for investigation.

Conclusion

This analysis represents the first instance of bibliometric scrutiny pertaining to circadian rhythm and its correlation with cardiovascular disease (CVD) through the use of visualization software. Notably, this study has succeeded in highlighting the recent research frontiers and prominent trajectories in this field, thereby providing a valuable contribution to the literature.

[Analysis of changes in intrinsic neural timescales in male smoking addicts based on whole brain resting-state functional magnetic resonance imaging]

Objective: To investigate the abnormal changes of intrinsic neural time scale (INT) in male smoking addicts based on whole brain resting state functional magnetic resonance imaging (rs-fMRI). Methods: A case-control study. The clinical data and whole brain rs-fMRI data of 139 male subjects, aged (34.1±8.8) years, recruited through the online platform from January 2019 to December 2021 were retrospectively analyzed. According to the existence of smoking addiction, they were divided into smoking addiction group (n=83) and healthy control group (n=56).INT was calculated to reflect the brain neural activity dynamics. Single sample t test was used to obtain the whole brain spatial distribution maps of INT in smoking addiction group and the control group. Then two-sample t test was conducted to explore the difference of INT between the smoking addition group and the healthy control group, with age and years of education as covariates. Finally, Spearman correlation analysis was used to explore the relationship between INT and nicotine dependence scale score and smoking index. Results: Subjects with smoking addiction and healthy control group showed a similar pattern of hierarchical neural timescales, namely shorter INT in sensorimotor areas and longer INT in parietal lobe, posterior cingulate cortex. In addition, in the smoking addiction group, the left medial occipital gyrus (peak t=-3.18), left suproccipital gyrus (peak t=-3.66), bilateral pericalar cleft cortex (left: peak t=-3.02, right: peak t=-3.22), bilateral lingual gyrus (left: peak t=-3.10, right: t peak=-3.04), left cuneus (peak t=-2.97), default network associated brain region [left anterior cuneus(peak t=-3.23), left angular gyrus (peak t=-3.07), and left posterior cingulate cortex (peak t=-3.54) were significantly lower than those of healthy controls (gaussian random field correction, voxel level all P<0.005, mass level all P<0.05). However, there was no significant correlation between INT and nicotine dependence scale score and smoking index (both P>0.05 after Bonferroni correction). Conclusion: Compared with healthy controls, smoking addicts showed abnormal changes in the dynamics of neural activity in the visual cortex and the default network.

[Colorectal adenocarcinoma with enteroblastic differentiation: a clinicopathological analysis of eight cases]

Objective: To investigate the clinicopathological features of colorectal adenocarcinoma with enteroblastic differentiation (CAED). Methods: Eight cases of CAED diagnosed at the Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China from January 2017 to August 2023 were collected. The histopathological, immunohistochemical, molecular and prognostic features of 8 CAED cases were analyzed. The relevant studies were also reviewed. Results: Among the eight patients, there were six males and two females, with an average age of 58 years (range: 29-77 years, median age: 61.5 years). Preoperative serum alpha-fetoprotein levels were elevated in five patients (14.0-286.6 μg/L). Four tumors were located in the colon, and four tumors in the rectum. Two patients were clinically staged as advanced stage (stage Ⅳ), and distant metastasis occurred at the initial diagnosis (one case had liver metastasis, and the other had lung, bone and multiple lymph nodes metastases). Six patients were clinically staged as locally-advanced stage (Stage Ⅱ-Ⅲ). Three of them developed distant metastases after surgery (one case had liver metastasis, one case had lung metastasis, and one case had peritoneal metastasis). Additionally, two patients died at 9 months and 24 months after surgery, respectively. The tumors were composed of various proportions of adenocarcinoma components with enteroblastic differentiation (30%-100%) and classical tubular adenocarcinoma components. The component with enteroblastic differentiation exhibited morphology similar to embryonic intestinal epithelium: cuboidal or columnar tumor cells arranged in tubular, papillary, cribriform, or solid nest patterns, with clear cytoplasm. Immunohistochemical studies showed that tumor cells expressed at least one oncofetal protein (SALL4, Glypican-3, and AFP). In addition, focal squamous differentiation was observed in 3 cases (3/8). Compared to the primary tumor, both CAED and squamous differentiation components were increased in the metastatic tumors. Based on the sequencing results of KRAS, NRAS and BRAF of the primary and/or metastatic tumors, 5 cases were wild-type, while KRAS exon 2 (G13D) mutations were identified in 2 cases. Conclusions: CAED is a rare colorectal malignancy with a dismal prognosis. Accurate pathological diagnosis is prognostically valuable. The histological features of enteroblastic differentiation, elevated serum AFP levels, and the expression of oncofetal proteins play an important role in the tumor diagnosis.

[Prediction of pathological remission of head and neck squamous cell carcinoma patients after neoadjuvant immunochemotherapy and construction of clinical model based on clinical features and inflammatory markers]

Objective: To analyze the potential clinical biological factors influencing the major pathological response (MPR) to neoadjuvant immunochemotherapy in patients with resectable head and neck squamous cell carcinoma (HNSCC). Methods: This retrospective study enrolled patients with resectable HNSCC who underwent neoadjuvant immunochemotherapy at Sun Yat-sen University Cancer Center from June 1, 2019 to December 31, 2021. Binary logistic regression was used to analyze the correlation between clinical characteristics, inflammatory markers and MPR, and a nomogram model was constructed. The calibration curve and decision curve analysis were used to verify the predictive ability and accuracy of the nomogram model. Results: A total of 173 patients were included in the study, with 141 males and 32 females, aged from 22 to 83 years. After pathological assessment, the patients were divided into two groups: MPR group (108 cases) and non MPR group (65 cases). Logistics regression analysis indicated that the patients with HPV+oropharyngeal cancer, partial response or complete response by imaging assessment, low pre-treatment platelet/lymphocyte ratio, low pre-treatment C reactive protein/albumin ratio and lower pre-and post-treatment C reactive protein/albumin ratio difference were more likely to have MPR (all P<0.05). Nomogram model was constructed based on the above factors, with a C-index of 0.826 (95%CI: 0.760-0.892), and the calibration curve and decision curve analysis confirmed the prediction accuracy of the model. Conclusion: This study shows that many factors are related to MPR of patients with resectable HNSCC receiving neoadjuvant immunochemotherapy and the constructed nomogram model helps to develop personalized treatment strategies for the patients.

Dynamics of magnetization at infinite temperature in a Heisenberg spin chain

Understanding universal aspects of quantum dynamics is an unresolved problem in statistical mechanics. In particular, the spin dynamics of the one-dimensional Heisenberg model were conjectured as to belong to the Kardar-Parisi-Zhang (KPZ) universality class based on the scaling of the infinite-temperature spin-spin correlation function. In a chain of 46 superconducting qubits, we studied the probability distribution of the magnetization transferred across the chain's center, [Formula: see text]. The first two moments of [Formula: see text] show superdiffusive behavior, a hallmark of KPZ universality. However, the third and fourth moments ruled out the KPZ conjecture and allow for evaluating other theories. Our results highlight the importance of studying higher moments in determining dynamic universality classes and provide insights into universal behavior in quantum systems.

Domestic wastewater sludge valorization: Multi-criteria evaluation of anaerobic digestion vs. hydrothermal liquefaction

The emerging hydrothermal liquefaction (HTL) process is evaluated against the classical anaerobic digestion (AD) processes for stabilizing wastewater sludges and recovering their energy- and nutrient-contents. Although HTL affords faster stabilization, better process stability, and liquid fuel and sterile fertilizer recovery, it suffers from higher energy demand and lower technology readiness level. For a rational comparison of these pathways, a multi-criteria evaluation is conducted considering 21 technical, environmental, economic, and social criteria. Criteria values for the HTL-pathway were derived from laboratory tests while those for the AD-pathway were compiled from literature. Of the 16 process alternatives evaluated, the AD-pathway including nitrogen-recovery by air-stripping and phosphorus recovery by the MEPHREC® process ranked first followed by the HTL-pathway. This multi-criteria study suggests that the HTL-pathway could be engineered as a superior alternative for sludge stabilization and resource recovery if phosphorus recovery and its technology readiness level could be improved.

Ordered Perovskite Structure with Functional Units for High Performance and Stable Solar Cells

Ion migration is one of the most critical challenges that affects the stability of metal-halide perovskite solar cells (PSCs). However, the current arsenal of available strategies for solving this issue is limited. Here, novel perovskite active layers following the concept of ordered structures with functional units (OSFU) to intrinsically suppress ion migration, in which a three-dimensional (3D) perovskite layer is deposited by vapor deposition for light absorption and a 2D layer is deposited by solution process for ion inhibition, are constructed. As a promising result, the activation energy of ion migration increases from 0.36 eV for the conventional perovskite to 0.54 eV for the OSFU perovskite. These devices exhibit substantially enhanced operational stability in comparison with the conventional ones, retaining >85% of their initial efficiencies after 1200 h under ISOS-L-1. Moreover, the OSFU devices show negligible fatigue behavior with a robust performance under light/dark cycling aging test (ISOS-LC-1 protocol), which demonstrates the promising application of functional motif theory in this field.

Imaging features of temporomandibular joint synovial chondromatosis with associated osseous degenerative changes

Synovial chondromatosis (SC) of the temporomandibular joint (TMJ) is a rare benign disease associated with the formation of multiple cartilaginous nodules in the synovial tissue of the TMJ. This can result in pain, swelling, clicking, limited mouth opening, and osseous degenerative joint changes. A retrospective cross-sectional study was performed to summarize the clinical features, radiographic findings, and surgical and histopathological findings of TMJ SC patients who underwent open surgery over a 24-year period. A radiographic scoring system was used to evaluate osseous changes and correlate condyle and joint fossa degeneration. The study included 38 patients and focused on 38 joints. All 38 of these joints showed degenerative changes in the condyle, while 37 showed osseous degenerative changes in the articular fossa. The degree of condylar degenerative changes was related to the duration of the chief complaints (r = 0.342, P = 0.036) and the histopathological stage of the TMJ SC (r = 0.440, P = 0.006), while the degree of joint fossa degenerative changes was associated with the radiographic extent of the SC (r = 0.504, P = 0.001), type of calcification (r = 0.365, P = 0.024), and the histopathological stage (r = 0.458, P = 0.004).

Antiviral effect of palmatine against infectious bronchitis virus through regulation of NF-κB/IRF7/JAK-STAT signalling pathway and apoptosis

1. Infectious bronchitis virus (IBV), a gamma-coronavirus, can infect chickens of all ages and leads to an acute contact respiratory infection. This study evaluated the anti-viral activity of palmatine, a natural non-flavonoid alkaloid, against IBV in chicken embryo kidney (CEK) cells.2. The half toxic concentration (CC50) of palmatine was 672.92 μM, the half inhibitory concentration (IC50) of palmatine against IBV was 7.76 μM and the selection index (SI) was 86.74.3. Mode of action assay showed that palmatine was able to directly inactivate IBV and inhibited the adsorption, penetration and intracellular replication of IBV.4. Palmatine significantly upregulated TRAF6, TAB1 and IKK-β compared with the IBV-infected group, leading to the increased expressions of pro-inflammatory cytokines IL-1β and TNF-α in the downstream NF-κB signalling pathway.5. Palmatine significantly up-regulated the levels of MDA5, MAVS, IRF7, IFN-α and IFN-β in the IRF7 pathway, inducing type I interferon production. It up-regulated the expression of 2'5'-oligoadenylate synthase (OAS) in the JAK-STAT pathway.6. IBV infection induced cell apoptosis and palmatine-treatment delayed the process of apoptosis by regulation of the expression of apoptosis-related genes (BAX, BCL-2, CASPASE-3 and CASPASE-8).7. Palmatine could exert anti-IBV activity through regulation of NF-κB/IRF7/JAK-STAT signalling pathways and apoptosis, providing a theoretical basis for the utilisation of palmatine to treat IBV infection.

Seedlings of Poncirus trifoliata exhibit tissue-specific detoxification in response to NH4 + toxicity

Ammonium nitrogen (NH4 +-N) is essential for fruit tree growth, but the impact of excess NH4 +-N from fertilizer on evergreen citrus trees is unclear. In a climate chamber, 8-month-old citrus plants were exposed to five different hydroponic NH4 +-N concentrations (0, 5, 10, 15 and 20 mm) for 1 month to study effects of NH4 +-N on growth characteristics, N uptake, metabolism, antioxidant enzymes and osmotic regulatory substances. Application of 10 mm NH4 +-N adversely affected root plasma membrane integrity, root physiological functions, and plant biomass. MDA, CAT, POD, APX and SOD content were significantly correlated with leaf N metabolic enzyme activity (GOGAT, GDH, GS and NR). GDH was the primary enzyme involved in NH4 +-N assimilation in leaves, while the primary pathway involved in roots was GS-GOGAT. Under comparatively high NH4 + addition, roots were the main organs involved in NH4 + utilization in citrus seedlings. Our results demonstrated that variations in NH4 + concentration and enzyme activity in various organs are associated with more effective N metabolism in roots than in leaves to prevent NH4 + toxicity in evergreen woody citrus plants. These results provide insight into the N forms used by citrus plants that are important for N fertilizer management.

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.

The impacts of exposure to risk factors during youth on the increasing global trend of early-onset pancreatic cancer

OBJECTIVES

An increasing trend of pancreatic cancer in young adults has emerged in some countries. This study aimed to investigate global trends of pancreatic cancer in young adults and explore the impact of exposure to risk factors on pancreatic cancer incidence during youth.

METHODS

Global and national data on pancreatic cancer incidence, disability-adjusted life-years, attributive mortality, and summary exposure values of risk factors were retrieved from the Global Burden of Disease 2019. The average annual percent change (AAPC) of incidence and mortality was calculated. Additionally, generalized additive models were applied to explore the non-linear associations between the levels and changes in the Human Development Index and AAPC.

RESULTS

Global pancreatic cancer incidence increased during various periods from 1990 to 2019, particularly in adults aged <45 years from 2010 to 2019, at an average annual increase rate of 0.7% (95% confidence interval: 0.4-1.0%). The AAPC of early-onset pancreatic cancer incidence from 2010 to 2019 was negatively correlated with Human Development Index levels in both 2010 and 2019 but positively correlated with Human Development Index acceleration. Significant increases in early-onset pancreatic cancer incidence were observed over this period in 32 of 88 countries, primarily in South America, North America, Oceania, and Africa. Early-onset pancreatic cancer mortality attributed to high body mass index and fasting plasma glucose increased, while that attributed to tobacco use declined.

CONCLUSIONS

An increasing trend has emerged in the global incidence and burden of early-onset pancreatic cancer over the last few decades. This rise may partly be attributed to global epidemics of high body mass index and fasting plasma glucose.

Effects of rumen-encapsulated methionine and lysine supplementation and low dietary protein on nitrogen efficiency and lactation performance of dairy cows

Low crude protein (CP) diets might be fed to dairy cows without affecting productivity if the balance of absorbed AA were improved, which would decrease the environmental effect of dairy farms. The aim of this study was to investigate the effects of supplementing ruminally protected Lys (RPL) and Met (RPM) at 2 levels of dietary CP on nutrient intake, milk production, milk composition, milk N efficiency (MNE), and plasma concentrations of AA in lactating Holstein cows and to evaluate these effects against the predictions of the new NASEM (2021) model. Fifteen multiparous cows were used in a replicated 3 × 3 Latin square design with 21-d periods. The 3 treatments were (1) a high-protein (HP) basal diet containing 16.4% CP (metabolizable protein [MP] balance of -130 g/d; 95% of target values), (2) a medium-protein diet containing 15% CP plus RPL (60 g/cow per day) and RPM (25 g/cow per day; MPLM; MP balance of -314 g/d; 87% of target values), and (3) a low-protein diet containing 13.6% CP plus RPL (60 g/cow per day) and RPM (25 g/cow per day; LPLM; MP balance of -479 g/d; 80% of target values). Dry matter intake was less for cows fed MPLM and LPLM diets compared with those fed the HP diet. Compared with the HP diet, the intake of CP, neutral detergent fiber, acid detergent fiber, and organic matter, but not starch, was lower for cows fed MPLM and LPLM diets. Milk production and composition were not affected by MPLM or LPLM diets relative to the HP diet. Milk urea N concentrations were reduced for the MPLM and LPLM diets compared with the HP diet, indicating that providing a low-protein diet supplemented with rumen-protected AA led to greater N efficiency. There was no significant effect of treatment on plasma AA concentrations except for proline, which significantly increased for the MPLM treatment compared with the other 2 treatments. Overall, the results supported the concept that milk performance might be maintained when feeding lactating dairy cows with low CP diets if the absorbed AA balance is maintained through RPL and RPM feeding. Further investigations are needed to evaluate responses over a longer time period with consideration of all AA rather than on the more aggregated MP and the ratio between Lys and Met.

Anti-aging Factor GRSF1 Attenuates Cerebral Ischemia-Reperfusion Injury in Mice by Inhibiting GPX4-Mediated Ferroptosis

Abnormal accumulation of senescent cells in tissues has been shown to facilitate the onset and progression of various diseases. As an important protein involving in the regulation of cellular senescence process, researches suggested GRSF1 as a potential senolytic target to improve multiple physiological and pathological processes. However, the underlying mechanism of cellular senescence on cerebral ischemia-reperfusion injury (CIRI) has not been revealed. Here, we investigated the effect of GRSF1 on CIRI and delved into its specific mechanisms. In the present study, we established a mouse model of cerebral ischemia-reperfusion (CIR) and observed low expression of anti-aging factor GRSF1, along with greatly increased levels of senescence-related markers p16 and p21 and senescence-associated secretory phenotype TNF-α. Furthermore, we found that the expression of GPX4 was elevated parallel to GRSF1 in CIR mice with overexpression of GRSF1, oxidative stress, and iron metabolism-related proteins were inhibited. Functionally, overexpressing GRSF1 significantly ameliorated infarct volume and neurological function scores and suppressed apoptosis in CIR mice, while administration of GPX4 inhibitors reversed these beneficial phenotypes. Taken together, our results indicate cellular senescence as an important pathological mechanism to exacerbate cerebral injury during CIRI, while GRSF1 could inhibit oxidative stress-mediated ferroptosis through upregulating GPX4 to attenuate reperfusion injury, which makes senolytic treatment, especially GRSF1, a promising therapeutic target for CIRI.

Effect of COVID-19 infection on pregnant women in plateau regions

OBJECTIVE

The present study aims to explore the effect of COVID-19 infection on pregnant women in plateau regions.

STUDY DESIGN

Data from 381 pregnant women infected with COVID-19 who underwent prenatal examination or treatment at Women and Children's Hospital of Tibet Autonomous Region between January 2020 and December 2022 and 314 pregnant women not infected with COVID-19 were retrospectively collected.

METHODS

The study participants were divided into an infected and non-infected group according to whether they were infected with COVID-19. Basic information (ethnicity, age, body mass index and gestational age [GA]), vaccination status, intensive care unit (ICU) admission and delivery outcomes were compared. Binary logistic regression was used to analyse the influencing factors of ICU admission.

RESULTS

The results revealed significant differences in the GA, vaccination rate, blood pressure, partial pressure of oxygen, white blood cell (WBC) count, ICU admission rate, preeclampsia rate, forearm presentation rate, thrombocytopenia rate, syphilis infection rate and placental abruption rate between the two groups (P < 0.05). A univariate analysis showed that COVID-19 infection, hepatitis B virus infection, the WBC count and hypoproteinaemia were risk factors for ICU admission. The results of the multivariate analysis of the ICU admission of pregnant women showed that COVID-19 infection (odds ratio [OR] = 4.271, 95 % confidence interval [CI]: 3.572-5.820, P < 0.05) was a risk factor for ICU admission and the WBC count (OR = 0.935, 95 % CI: 0.874-0.947, P < 0.05) was a protective factor for ICU admission.

CONCLUSION

Pregnant women are vulnerable to the adverse consequences of COVID-19 infection, and public health measures such as vaccination are needed to protect this population subgroup.

Factors influencing family resilience in adult patients with acute leukemia undergoing chemotherapy: A qualitative study

Objective

To explore the factors influencing family resilience in adult patients with acute leukemia undergoing chemotherapy, with the aim of providing a theoretical basis for the development of strategies to strengthen their family resilience.

Methods

A descriptive phenomenological qualitative research method was used to select 11 adult acute leukemia chemotherapy patients for semi-structured interviews. Colaizzi 7-step analysis and NVivo 12.0 were used to summarize information and refine themes.

Results

The main outcomes consisted of two themes and 11 sub-themes: protective factors for family resilience (positive traits, cognitive restructuring, positive family beliefs, organizational flexibility, clear communication, and social support) and risk factors for family resilience (symptom burden, self-concealment, role overload, economic distress, and social alienation).

Conclusions

Health care professionals should pay attention to screening protective and risk factors for family resilience in adult acute leukemia chemotherapy patients, affirming the positive role of internal and external resources available in the family in stressful situations, alleviating patients' negative experiences, and promoting the recovery of family function.

A Bilayer Method for Measuring Toughness and Strength of Dental Ceramics

The ever-increasing usage of ceramic materials in restorative dentistry necessitates a simple and effective method to evaluate flexural strength σF and fracture toughness KC. We propose a novel method to determine these quantities using a bilayer specimen composed of a brittle plate adhesively bonded onto a transparent polycarbonate substrate. When this bilayer structure is placed under spherical indentation, tunneling radial cracks initiate and propagate in the lower surface of the brittle layer. The failure analysis is based on previous theoretical relationships, which correlate σF with the indentation force P and layer thickness d, and KC with P and mean length of radial cracks. This work examines the accuracy and limitations of this approach using a wide range of contemporary dental ceramic materials. The effect of layer thickness, indenter radius, load level, and length and number of radial cracks are carefully examined. The accuracy of the predicted σF and KC is similar to those obtained with other concurrent test methods, such as biaxial flexure and 3-point bending (σF), and bending specimens with crack-initiation flaws (KC). The benefits of the present approach include treatment for small and thin plates, elimination of the need to introduce a precrack, and avoidance of dealing with local material nonlinearity effects for the KC measurements. Finally, the bilayer configuration resembles occlusal loading of a ceramic restoration (brittle layer) bonded to a posterior tooth (compliant substrate).

Comparative investigation of transport and deposition of nebulized particles in nasal airways following various middle turbinectomy

BACKGROUND

Topical intranasal medication is required following functional endoscopic sinus surgery (FESS). The optimal particle size of transnasal nebulization aimed at the sinonasal cavities is not conclusive. The current study aims to evaluate the effect of particle size and various surgery scope of middle turbinectomy (MT) on post-full FESS drug delivery to the sinonasal cavities.

METHODS

Sinonasal reconstructions were performed from post-full FESS CT scans in 6 chronic rhinosinusitis with nasal polyps (CRSwNP) patients. Four additional models representing alternative surgery scopes of MT were established from each post-FESS reconstruction for simulation data comparison. Airflow and particle deposition of nebulized delivery were simulated via computational fluid dynamics (CFD) and validated through in vitro experiments. The optimal particle sizes reaching a deposition of at least 75% of the maximum in the targeted regions were identified.

RESULTS

The drug deposition rate onto the targeted regions increased following MT, with the greatest deposition following posterior MT (P-MT). Droplets in the range of 18-26 μm reached a deposition of larger than 75% of the maximum onto the targeted regions. Drug delivery rate in the sinonasal cavities varied significantly among individuals and across different types of MT with varying surgical scopes.

CONCLUSIONS

This study is the first to investigate the effect of various surgery scope on drug delivery by transnasal nebulization to the sinonasal cavities. The findings strongly affirm the vast potential of transnasal nebulization as an effective post-FESS treatment option. Moreover, it emphasizes that the drug delivery process via atomizers to the nasal cavity and paranasal sinuses is highly sensitive to the particle size.

Crude Tieguanyin oolong tea polysaccharides regulate intestinal immune and gut microflora in dextran sulfate sodium-induced mice colitis

BACKGROUND

The global incidence and prevalence of inflammatory bowel diseases (IBDs) have been increasing. Epidemiological studies, clinical trials, and animal experiments have indicated a negative association between the consumption of tea and IBD. This study aims to investigate the protective effects of crude Tieguanyin oolong tea polysaccharides (CTPS) on experimental colitis, while also exploring the underlying mechanisms.

RESULTS

The administration of CTPS significantly alleviated IBD in the mouse model, and was found to regulate T-cell mediated immune responses in the colon by modulating cytokine production associated with T cells. Furthermore, CTPS demonstrated a positive impact on the gut microbiota, reversing the increase in pathogenic Helicobacter and enhancing the relative abundances of beneficial bacteria such as Akkermansia, Lachnospiraceae, and Odoribacter. Oral administration of CTPS also led to an improvement in intestinal metabolism, specifically by increasing the levels of short-chain fatty acids.

CONCLUSION

This study provides the first in vivo evidence of the protective effects of CTPS on colitis in mice. The effects are likely facilitated through the regulation of T cell-mediated responses and modulation of the gut microbiota, suggesting that CTPS may be a potential preventive and therapeutic approach for IBD. © 2023 Society of Chemical Industry.

Amplitude Analysis of the B^{0}→K^{*0}μ^{+}μ^{-} Decay

An amplitude analysis of the B^{0}→K^{*0}μ^{+}μ^{-} decay is presented using a dataset corresponding to an integrated luminosity of 4.7  fb^{-1} of pp collision data collected with the LHCb experiment. For the first time, the coefficients associated to short-distance physics effects, sensitive to processes beyond the standard model, are extracted directly from the data through a q^{2}-unbinned amplitude analysis, where q^{2} is the μ^{+}μ^{-} invariant mass squared. Long-distance contributions, which originate from nonfactorizable QCD processes, are systematically investigated, and the most accurate assessment to date of their impact on the physical observables is obtained. The pattern of measured corrections to the short-distance couplings is found to be consistent with previous analyses of b- to s-quark transitions, with the largest discrepancy from the standard model predictions found to be at the level of 1.8 standard deviations. The global significance of the observed differences in the decay is 1.4 standard deviations.

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

Key Words Collapse

MESH Headings Collapse

Grants Collapse

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

Collapse

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.

Long-Term Bonding Efficacy of CAD/CAM Hybrid Restorative Materials and Universal Adhesives

OBJECTIVES

In-office and lab milled prostheses are the staple for indirect restorations. It is therefore critical to determine their long-term bonding durability.

METHODS

CAD/ CAM blocks of two classes of restorative materials: 1) a nano-ceramic reinforced polymer matrix (NCPM) and, 2) a polymer-infiltrated ceramic network (PICN) were bonded using four different universal adhesives (UA) and silane systems. A lithium disilicate glassceramic (LDS) was used as a reference. The blocks were bisected and bonded with different UA/resin-cement pairs. Bonded blocks were then cut into 1.0x1.0x12.0 mm bar specimens for microtensile bond testing. Half the bars were subjected to bond strength testing immediately and the other half after aging by 50,000 thermal cycles between 5°C and 55°C. ANOVA and post-hoc tests were used to compare mean bond strength among groups.

RESULTS

NCPM presented consistently high bond strength regardless of bonding techniques, while the bond strength of PICN and LDS were lower when bonded with UA relative to traditional silanes. The more hydrophilic UA produced higher bond strengths.

DISCUSSION

Glass-ceramics exhibited lower bond strength with UA than the conventional etch-rinse-silane techniques. However, UAs preserved bonding interface in the long-term.

SIGNIFICANCE

NCPM displayed superior bond strength relative to PICN and LDS regardless of the type of adhesives and bonding techniques.

[Clinical and genetic characteristics of 21 children with Rubinstein-Taybi syndrome]

Objective: To investigate the phenotypes of Rubinstein-Taybi syndrome (RSTS) caused by variants in the CREBBP or EP300 gene, and the correlation between genotype and phenotype. Methods: This case series study was performed on pediatric patients who were referred to the Children's Hospital of Capital Institute of Pediatrics between January 2013 and July 2022. Both point variant and copy number deletion in CREBBP or EP300 gene were detected by whole exome sequencing, chromosomal microarray analysis, or copy number variation sequencing (CNV-seq). The variant categories were summarized and phenotype numbers were re-visited for RSTS patients. Based on variant types, the patients were divided into different groups (point variant or copy number deletion, EP300 or CREBBP point variant, and loss of function or missense variant). Phenotype counts between different groups were compared using the rank-sum test of two independent samples. Results: A total of 21 RSTS patients were recruited, including 12 males and 9 females, with ages ranging from 1 month to 14 years and 2 months. Among them, 67% (14/21) had point variants, and 33% (7/21) had copy number deletions. Out of these, 20 variants (95%) were de novo. Among 20 patients finishing phenotype count during re-visit, 95% (19/20) of the patients exhibited developmental delays before the age of 2 years. Additionally, 80% (16/20) of the patients had distinctive facial features. Considering phenotype count, no statistically significant difference was found between point variant (14 cases) and copy number deletion (6 cases) (5.0 (3.0, 7.0) vs. 5.0 (2.5, 5.3), Z=0.75, P=0.452), CREBBP (10 cases) and EP300 gene (4 cases) point variant (5.0 (3.8, 7.0) vs. 4.0 (2.0, 6.0), Z=1.14, P=0.253), and loss of function (9 cases) and missense (5 cases) variant (6.0 (4.5, 7.0) vs. 3.0 (2.5, 5.5), Z=1.54, P=0.121). Conclusions: Patients with RSTS primarily exhibit developmental delays in early childhood. Specific facial features serve as suggested signs of genetic testing. However, no significant genotype-phenotype correlation is found.

[Exploration of the method and efficacy of treatments for intractable pelvic pain caused by rectal or bladder fistula]

Objective: To explore the causes and therapeutic effects of pelvic pain caused by rectal fistula or bladder fistula after comprehensive treatment of cervical cancer and rectal cancer (radiotherapy, surgery, chemotherapy, and other treatments). Methods: A retrospective analysis was conducted on the clinical and pathological data of patients with pelvic tumors admitted to the First People's Hospital of Yinchuan City, Ningxia and the Affiliated Cancer Hospital of Zhengzhou University from June 2016 to June 2022. The causes of persistent pelvic pain in patients after comprehensive treatment was investigated, and the corresponding therapeutic effects after clinical treatment was observed. Results: Thirty-two tumor patients experienced persistent pain after comprehensive treatment, including 22 cases of cervical cancer and 10 cases of rectal cancer. The preoperative pain of the entire group of patients was evaluated using the digital grading method, with a pain score of (7.88±1.31) points. Among the 32 patients, there were 16 cases of rectovaginal fistula or ileovaginal fistula, 9 cases of vesicovaginal fistula, 5 cases of rectoperineal fistula, and 2 cases of vesicovaginorectal fistula. Thirty-two patients were initially treated with medication to relieve pain, and according to the ruptured organs, a fistula was made to the corresponding proximal intestinal canal and renal pelvis to intercept the intestinal contents and urine. However, the pain did not significantly be improved. The pain score of treatment with the above methods for one week was (8.13±1.13) points, and there was no statistically significant difference compared to preoperative treatment (P=0.417). In the later stage, based on a comprehensive evaluation of whether the tumor had recurred, the value of organ preservation, the benefits of surgery, the balance between survival time and improving quality of life, pathological organ resection or repair was performed. The surgical methods included repair of leaks, local debridement combined with irrigation of proximal intestinal fluid, distal closure of the sigmoid colon combined with proximal ostomy, posterior pelvic organ resection, anterior pelvic organ resection, and total pelvic organ resection. One week after surgery, the patients' pain completely relieved or disappeared, with the pain score of (1.72±1.37) points, which was significantly divergent from the preoperative and initial surgical treatments (P＜0.001). Conclusions: Palliative pyelostomy and proximal enterostomy cannot effectively alleviate persistent pelvic floor pain. The fundamental way to alleviate pain is complete blocking of the inflammatory erosion of the intestinal fluid and urine.

Stable quantum-correlated many-body states through engineered dissipation

Engineered dissipative reservoirs have the potential to steer many-body quantum systems toward correlated steady states useful for quantum simulation of high-temperature superconductivity or quantum magnetism. Using up to 49 superconducting qubits, we prepared low-energy states of the transverse-field Ising model through coupling to dissipative auxiliary qubits. In one dimension, we observed long-range quantum correlations and a ground-state fidelity of 0.86 for 18 qubits at the critical point. In two dimensions, we found mutual information that extends beyond nearest neighbors. Lastly, by coupling the system to auxiliaries emulating reservoirs with different chemical potentials, we explored transport in the quantum Heisenberg model. Our results establish engineered dissipation as a scalable alternative to unitary evolution for preparing entangled many-body states on noisy quantum processors.

Quality assessment of health science-related short videos on TikTok: A scoping review

OBJECTIVE

The aims of this review are to clarify the current state of research in terms of assessment tools and assessors of the quality of health science-related short videos on TikTok, to identify limitations in existing research; and to provide a reference for future studies.

METHODS

A scoping review was conducted. The Cochrane Library, PubMed, MEDLINE, Web of Science, Embase, Scopus, EBSCO, CNKI, VIP, Wanfang Data, and CBM databases were searched from September 2016 to November 2022. Manual searching was also performed to identify additional eligible studies. A total of 2620 documents were initially retrieved, and 29 were ultimately included. The literature was screened and collected, and data were extracted and summarized by 2 researchers.

RESULTS

(1) The quality evaluation tools used in the 29 papers included the DISCERN, PEMAT(A/V), GQS, JAMA, HONcode, guidelines and self-developed tools. Twenty-four of the included articles used the DISCERN for quality assessment, which was the most frequently used evaluation tool. However, most of these tools were not developed to assess health science-related short videos, lacked credibility tests, and had poor applicability; therefore, the accuracy of the evaluation results might be biased. (2) The assessors of the quality of health science-related short videos on TikTok were mainly experts in related fields and medical students, with doctors (12/14) being the most common evaluators. Fifteen studies did not report the identity of the evaluators, and 12 studies did not report interrater reliability.

CONCLUSION

This scoping review found that there is a lack of specific quality assessment tools for health science-related short videos on TikTok. Second, the current quality assessors of health science-related short videos on TikTok are limited. Future research should focus on the development of reliable, scientific quality assessment tools for health science-related short videos; unifying the evaluation standards; inviting users with different backgrounds and different health literacy levels to conduct quality assessments; exploring the quality assessment of health science-related short videos on TikTok from different perspectives.

Observation of WWγ Production and Search for Hγ Production in Proton-Proton Collisions at sqrt[s]=13 TeV

The observation of WWγ production in proton-proton collisions at a center-of-mass energy of 13 TeV with an integrated luminosity of 138  fb^{-1} is presented. The observed (expected) significance is 5.6 (5.1) standard deviations. Events are selected by requiring exactly two leptons (one electron and one muon) of opposite charge, moderate missing transverse momentum, and a photon. The measured fiducial cross section for WWγ is 5.9±0.8(stat)±0.8(syst)±0.7(modeling)  fb, in agreement with the next-to-leading order quantum chromodynamics prediction. The analysis is extended with a search for the associated production of the Higgs boson and a photon, which is generated by a coupling of the Higgs boson to light quarks. The result is used to constrain the Higgs boson couplings to light quarks.

[Surveillance of echinococcosis in Bayingolin Mongol Autonomous Prefecture, Xinjiang Uygur Autonomous Region from 2017 to 2022]

OBJECTIVE

To analyze the echinococcosis surveillance results in Bayingolin Mongol Autonomous Prefecture, Xinjiang Uygur Autonomous Region from 2017 to 2022, so as to provide insights into formulation of echinococcosis control measures in the prefecture.

METHODS

Villagers were randomly sampled using a multistage sampling method from class I and II echinococcosis endemic counties in Bayingolin Mongolian Autonomous Prefecture from 2017 to 2022 for detection of human echinococcosis, while all patients undergoing ultrasound examinations in medical institutions in class III endemic counties received active echinococcosis screening. In addition, livestock in centralized slaughterhouses or slaughtering sites were screened for echinococcosis using the palpation and necropsy method, and fresh domestic dog feces samples were collected from randomly selected dog owners in each administrative village for detection of Echinococcus copro-antigen in domestic dogs. The trends in detection of human and livestock echinococcosis, detection of newly diagnosed human echinococcosis cases and detection of Echinococcus coproantigen in domestic dogs were analyzed in Bayingolin Mongol Autonomous Prefecture from 2017 to 2022.

RESULTS

The mean detection rate of human echinococcosis was 0.13% (540/407 803) in Bayingolin Mongol Autonomous Prefecture from 2017 to 2022, which appeared a tendency towards a decline over years (χ2trend = 1 217.21, P < 0.001), and the highest detection of newly diagnosed echinococcosis cases was seen in Hejing County (0.28%, 191/67 865). The detection of livestock echinococcosis appeared a tendency towards a decline over years from 2017 to 2022 (χ2trend = 147.02, P < 0.001), with the highest detection rate seen in Hejing County (3.44%, 86/2 500), and the detection of Echinococcus copro-antigen in domestic dogs appeared a tendency towards a decline over years from 2017 to 2022 (χ2trend = 302.46, P < 0.001), with the highest detection rate in Qiemo County (2.74%, 118/4 313).

CONCLUSIONS

The detection of human and livestock echinococcosis and dog feces antigens Echinococcus copro-antigen in domestic dogs all appeared a tendency towards a decline in Bayingolin Mongol Autonomous Prefecture, Xinjiang Uygur Autonomous Region from 2017 to 2022; however, there is still a high echinococcosis transmission risk in local areas. Sustainable integrated echinococcosis control is required in Bayingolin Mongol Autonomous Prefecture.

Drought priming-induced stress memory improves subsequent drought or heat tolerance via activation of γ-aminobutyric acid-regulated pathways in creeping bentgrass

Recurrent drought can induce stress memory in plants to induce tolerance to subsequent stress, such as high temperature or drought. Drought priming (DP) is an effective approach to improve tolerance to various stresses; however, the potential mechanism of DP-induced stress memory has not been fully resoved. We examined DP-regulated subsequent drought tolerance or thermotolerance associated with changes in physiological responses, GABA and NO metabolism, heat shock factor (HSF) and dehydrin (DHN) pathways in perennial creeping bentgrass. Plants can recover after two cycle of DP, and DP-treated plants had significantly higher tolerance to subsequent drought or heat stress, with higher leaf RWC, Chl content, photochemical efficiency, and cell membrane stability. DP significantly alleviated oxidative damage through enhancing total antioxidant capacity in response to subsequent drought or heat stress. Endogenous GABA was significantly increased by DP through activating glutamic acid decarboxylase activity and inhibiting GABA transaminase activity. DP also enhanced accumulation of NO, depending on NOS activity, under subsequent drought or heat stress. Transcript levels of multiple transcription factors, heat shock proteins, and DHNs in the HSF and DHN pathways were up-regulated by DP under drought or heat stress, but there were differences between DP-regulated heat tolerance and drought tolerance in these pathways. The findings indicate that under recurrent moderate drought, DP improves subsequent tolerance to drought or heat stress in relation to GABA-regulated pathways, providing new insight into understanding of the role of stress memory in plant adaptation to complex environmental stresses.

Strictureplasty may lead to increased preference in the surgical management of Crohn's disease: a case-matched study

BACKGROUND

Resection and strictureplasty are the two surgical modalities used in the management of Crohn's disease (CD). The objective of this study was to compare morbidity and clinical recurrence between patients who underwent strictureplasty and patients who underwent resection.

METHODS

Patients with CD who underwent strictureplasty between January 2012 and December 2022 were enrolled. The patients were well matched with patients who underwent resection without strictureplasty. Patient- and disease-specific characteristics, postoperative morbidity, and clinical recurrence were also analyzed.

RESULTS

A total of 118 patients who underwent a total of 192 strictureplasties were well matched to 118 patients who underwent resection. The strictureplasty group exhibited significantly less blood loss (30 ml versus 50 ml, p < 0.001) and stoma creation (2.5% versus 16.9%, p < 0.001). No significant difference was found regarding postoperative complications or length of postoperative stay. At the end of the follow-up, the overall rate of clinical recurrence was 39.4%, and no difference was observed between the two groups. Postoperative prophylactic use of biologics (odds ratio = 0.2, p < 0.001) was the only protective factor against recurrence.

CONCLUSION

Strictureplasty does not increase the risk of complications or recurrence compared with resection. It represents a viable alternative to resection in selected patients, and as such, it should have a broader scope of indications and greater acceptance among surgeons.

[Multicenter retrospect analysis of early clinical features and analysis of risk factors on prognosis of elderly patients with severe burns]

Objective: To investigate the early clinical characteristics of elderly patients with severe burns and the risk factors on prognosis. Methods: This study was a retrospective case series study. Clinical data of 124 elderly patients with severe burns who met the inclusion criteria and were admitted to the 12 hospitals from January 2015 to December 2020 were collected, including 4 patients from the Fourth People's Hospital of Dalian, 5 patients from Fujian Medical University Union Hospital, 22 patients from Guangzhou Red Cross Hospital of Jinan University, 5 patients from Heilongjiang Provincial Hospital, 27 patients from the First Affiliated Hospital of Naval Medical University, 9 patients from the First Affiliated Hospital of Nanchang University, 10 patients from Affiliated Hospital of Nantong University, 9 patients from Tongren Hospital of Wuhan University & Wuhan Third Hospital, 12 patients from the 924th Hospital of PLA, 6 patients from Zhangjiagang First People's Hospital, 4 patients from Taizhou Hospital of Zhejiang Province, and 11 patients from Zhengzhou First People's Hospital. The patients' overall clinical characteristics, such as gender, age, body mass index, total burn area, full-thickness burn area, inhalation injury, causative factors, whether combined with underlying medical diseases, and admission time after injury were recorded. According to the survival outcome within 28 days after injury, the patients were divided into survival group (89 cases) and death group (35 cases). The following data of patients were compared between the two groups, including the basic data and injuries (the same as the overall clinical characteristics ahead); the coagulation indexes within the first 24 hours of injury such as prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time, D-dimer, fibrinogen degradation product (FDP), international normalized ratio (INR), and fibrinogen; the blood routine indexes within the first 24 hours of injury such as white blood cell count, platelet count, neutrophil-to-lymphocyte ratio, monocyte count, red blood cell count, hemoglobin, and hematocrit; the organ function indexes within the first 24 hours of injury such as direct bilirubin, total bilirubin, urea, serum creatinine, aspartate aminotransferase, alanine aminotransferase, total protein, albumin, globulin, blood glucose, triglyceride, total cholesterol, alkaline phosphatase, creatine kinase, electrolyte indexes (potassium, sodium, chlorine, calcium, magnesium, and phosphorus in blood), uric acid, myoglobin, and brain natriuretic peptide; the infection and blood gas indexes within the first 24 hours of injury such as procalcitonin, C-reactive protein, pH value, oxygenation index, base excess, and lactate; treatment such as whether conducted with mechanical ventilation, whether conducted with continuous renal replacement therapy, whether conducted with anticoagulation therapy, whether applied with vasoactive drugs, and fluid resuscitation. The analysis was conducted to screen the independent risk factors for the mortality within 28 days after injury in elderly patients with severe burns. Results: Among 124 patients, there were 82 males and 42 females, aged 60-97 years, with body mass index of 23.44 (21.09, 25.95) kg/m2, total burn area of 54.00% (42.00%, 75.00%) total body surface area (TBSA), and full-thickness burn area of 25.00% (10.00%, 40.00%) TBSA. The patients were mainly combined with moderate to severe inhalation injury and caused by flame burns. There were 43 cases with underlying medical diseases. The majority of patients were admitted to the hospital within 8 hours after injury. There were statistically significant differences between patients in the 2 groups in terms of age, total burn area, full-thickness burn area, and inhalation injury, and PT, APTT, D-dimer, FDP, INR, white blood cell count, platelet count, urea, serum creatinine, blood glucose, blood sodium, uric acid, myoglobin, and urine volume within the first 24 hours of injury (with Z values of 2.37, 5.49, 5.26, 5.97, 2.18, 1.95, 2.68, 2.68, 2.51, 2.82, 2.14, 3.40, 5.31, 3.41, 2.35, 3.81, 2.16, and -3.82, respectively, P<0.05); there were statistically significant differences between two groups of patients in whether conducted with mechanical ventilation and whether applied with vasoactive drugs (with χ2 values of 9.44 and 28.50, respectively, P<0.05). Age, total burn area, full-thickness burn area, serum creatinine within the first 24 hours of injury, and APTT within the first 24 hours of injury were the independent risk factors for the mortality within 28 days after injury in elderly patients with severe burns (with odds ratios of 1.17, 1.10, 1.10, 1.09, and 1.27, 95% confidence intervals of 1.03-1.40, 1.04-1.21, 1.05-1.19, 1.05-1.17, and 1.07-1.69, respectively, P<0.05). Conclusions: The elderly patients with severe burns had the injuries mainly from flame burns, often accompanied by moderate to severe inhalation injury and enhanced inflammatory response, elevated blood glucose levels, activated fibrinolysis, and impaired organ function in the early stage, which are associated with their prognosis. Age, total burn area, full-thickness burn area, and serum creatinine and APTT within the first 24 hours of injury are the independent risk factors for death within 28 days after injury in this population.

Review: Mechanism, effectiveness, and the prospects of medicinal plants and their bioactive compounds in lowering ruminants' enteric methane emission

Animal nutritionists continue to investigate new strategies to combat the challenge of methane emissions from ruminants. Medicinal plants (MPs) are known to be beneficial to animal health and exert functional roles in livestock due to their phytogenic compounds with antimicrobial, immunostimulatory, antioxidative, and anti-inflammatory activities. Some MP has been reported to be anti-methanogenic and can effectively lower ruminants' enteric methane emissions. This review overviews trends in MP utilization in ruminants, their bioactivity and their effectiveness in lowering enteric methane production. It highlights the MP regulatory mechanism and the gaps that must be critically addressed to improve its efficacy. MP could reduce enteric methane production by up to 8-50% by regulating the rumen fermentation pathway, directing hydrogen toward propionogenesis, and modifying rumen diversity, structure, and population of the methanogens and protozoa. Yet, factors such as palatability, extraction techniques, and economic implications must be further considered to exploit their potential fully.

Rhesus infant nervous temperament predicts peri-adolescent central amygdala metabolism & behavioral inhibition measured by a machine-learning approach

Anxiety disorders affect millions of people worldwide and impair health, happiness, and productivity on a massive scale. Developmental research points to a connection between early-life behavioral inhibition and the eventual development of these disorders. Our group has previously shown that measures of behavioral inhibition in young rhesus monkeys (Macaca mulatta) predict anxiety-like behavior later in life. In recent years, clinical and basic researchers have implicated the central extended amygdala (EAc)-a neuroanatomical concept that includes the central nucleus of the amygdala (Ce) and the bed nucleus of the stria terminalis (BST)-as a key neural substrate for the expression of anxious and inhibited behavior. An improved understanding of how early-life behavioral inhibition relates to an increased lifetime risk of anxiety disorders-and how this relationship is mediated by alterations in the EAc-could lead to improved treatments and preventive strategies. In this study, we explored the relationships between infant behavioral inhibition and peri-adolescent defensive behavior and brain metabolism in 18 female rhesus monkeys. We coupled a mildly threatening behavioral assay with concurrent multimodal neuroimaging, and related those findings to various measures of infant temperament. To score the behavioral assay, we developed and validated UC-Freeze, a semi-automated machine-learning (ML) tool that uses unsupervised clustering to quantify freezing. Consistent with previous work, we found that heightened Ce metabolism predicted elevated defensive behavior (i.e., more freezing) in the presence of an unfamiliar human intruder. Although we found no link between infant-inhibited temperament and peri-adolescent EAc metabolism or defensive behavior, we did identify infant nervous temperament as a significant predictor of peri-adolescent defensive behavior. Our findings suggest a connection between infant nervous temperament and the eventual development of anxiety and depressive disorders. Moreover, our approach highlights the potential for ML tools to augment existing behavioral neuroscience methods.

New Structures in the J/ψJ/ψ Mass Spectrum in Proton-Proton Collisions at sqrt[s]=13 TeV

A search is reported for near-threshold structures in the J/ψJ/ψ invariant mass spectrum produced in proton-proton collisions at sqrt[s]=13  TeV from data collected by the CMS experiment, corresponding to an integrated luminosity of 135  fb^{-1}. Three structures are found, and a model with quantum interference among these structures provides a good description of the data. A new structure is observed with a local significance above 5 standard deviations at a mass of 6638_{-38}^{+43}(stat)_{-31}^{+16}(syst)  MeV. Another structure with even higher significance is found at a mass of 6847_{-28}^{+44}(stat)_{-20}^{+48}(syst)  MeV, which is consistent with the X(6900) resonance reported by the LHCb experiment and confirmed by the ATLAS experiment. Evidence for another new structure, with a local significance of 4.7 standard deviations, is found at a mass of 7134_{-25}^{+48}(stat)_{-15}^{+41}(syst)  MeV. Results are also reported for a model without interference, which does not fit the data as well and shows mass shifts up to 150 MeV relative to the model with interference.

FLASH radiotherapy for the treatment of symptomatic bone metastases in the thorax (FAST-02): protocol for a prospective study of a novel radiotherapy approach

BACKGROUND

FLASH therapy is a treatment technique in which radiation is delivered at ultra-high dose rates (≥ 40 Gy/s). The first-in-human FAST-01 clinical trial demonstrated the clinical feasibility of proton FLASH in the treatment of extremity bone metastases. The objectives of this investigation are to assess the toxicities of treatment and pain relief in study participants with painful thoracic bone metastases treated with FLASH radiotherapy, as well as workflow metrics in a clinical setting.

METHODS

This single-arm clinical trial is being conducted under an FDA investigational device exemption (IDE) approved for 10 patients with 1-3 painful bone metastases in the thorax, excluding bone metastases in the spine. Treatment will be 8 Gy in a single fraction administered at ≥ 40 Gy/s on a FLASH-enabled proton therapy system delivering a single transmission proton beam. Primary study endpoints are efficacy (pain relief) and safety. Patient questionnaires evaluating pain flare at the treatment site will be completed for 10 consecutive days post-RT. Pain response and adverse events (AEs) will be evaluated on the day of treatment and on day 7, day 15, months 1, 2, 3, 6, 9, and 12, and every 6 months thereafter. The outcomes for clinical workflow feasibility are the occurrence of any device issues as well as time on the treatment table.

DISCUSSION

This prospective clinical trial will provide clinical data for evaluating the efficacy and safety of proton FLASH for palliation of bony metastases in the thorax. Positive findings will support the further exploration of FLASH radiation for other clinical indications including patient populations treated with curative intent.

REGISTRATION

ClinicalTrials.gov NCT05524064.

[The application of setting tube voltage and iodine delivery rate in weight-grouped for reducing the radiation and contrast medium dose in coronary CT angiography]

Objective: To evaluate the application value of reducing tube voltage and iodine delivery rate according to body weight in coronary CT angiography (CCTA). Methods: A prospective randomized controlled study. A total of 297 subjects, 172 males and 125 females, aged [M (Q1, Q3)]60.0 (50.0, 68.0) years, who underwent CCTA examination in Peking University Third Hospital due to clinically suspected coronary heart disease from May to December 2022 were included. According to the odd or even visit dates, the subjects were randomly divided into test group (n=156) and control group (n=141). The subjects in both groups were divided into four sub-groups according to body weight: 50-59 group, 60-69 kg group, 70-79 kg group and 80-89 kg group, respectively. The CCTA images were reconstructed with hybrid iterative algorithm(KARL 3D) with levels of 6 and 8, respectively. 100 kVp and iodine flow rate 1.1, 1.3, 1.4 and 1.5 gI/s recommended by the domestic CCTA application guidelines were used in the control group, while the tube voltage and iodine flow rate were reduced in the test group based on the guidelines and body weight:70 kVp and 0.8 g I/s in 50~59 kg group, 80 kVp and 1.0 gI/s in 60~69 kg group, 80 kVp and 1.1 gI/s in70~79 kg group, and 100 kVp and 1.5 gI/s in 80~89 kg group, respectively. The CT values and standard deviation (SD) of aortic root, proximal left anterior descending branch (LAD) and distal right coronary artery (RCA) luminal CCTA, the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of coronary artery CT images, subjective coronary scores and effective radiation dose (ED) were compared between the both groups. One-way ANOVA or Wilcoxon test was used to analyze the differences of above indicators between the groups to evaluate the application value of low voltage and low iodine flow rate based on weight in coronary CCTA. Results: CT values of aortic root, LAD proximal CT values and SD values of aortic root [411.4 (377.2, 439.8) HU, (366.3±42.9) HU, 26.5±2.3] in the test group were all higher than those in the control group [379.00 (335.2, 415.9) HU, (355.0±46.9) HU and 24.8±2.3]. The differences were statistically significant (all P<0.05), and the other parameters were not statistically significant (all P>0.05). The total subjective image quality score in test group were superior to those in the control group (all P<0.05). The total ED and contrast agent dosage [2.07 (1.52, 3.28) mSv and (38.28±9.68) ml] in CCTA examination in the test group were lower than those in the control group [3.30(2.32, 4.44) mSv and (45.31±5.63) ml], and the differences were statistically significant (all P<0.05). The dosage of ED and contrast agent in the test group was decreased by 37.3% and 15.5%, respectively. Conclusion: Combined with KARL 3D,it is feasible to reduce contrast medium and ED by setting the tube voltage and iodine flow rate of CCTA according to the weight of the subject, which can further reduce the radiation dose and contrast agent dosage of CCTA.

[Clinical observation of the intraocular distribution characteristics of indocyanine green after epiretinal membrane peeling using a fluorescence detection system developed in Python]

Objective: To utilize a Python-based fluorescence area detection system to observe and quantitatively analyze the intraocular distribution characteristics and metabolic patterns of Indocyanine Green (ICG) following epiretinal membrane peeling. Methods: A prospective case series study was conducted on patients with idiopathic epiretinal membrane undergoing vitrectomy at West China Hospital of Sichuan University from March 2019 to March 2021. ICG staining was applied during surgery for peeling the epiretinal membrane and internal limiting membrane. Patients were followed up at 1 week, 1 month, 3 months, 6 months, and 12 months postoperatively, with assessments including best-corrected visual acuity, intraocular pressure, fundus photography, near-infrared fundus fluorescence imaging (NIR-FF), and optical coherence tomography (OCT). A Python-based ICG intraocular metabolism detection system was developed to measure the residual area of ICG fluorescence on NIR-FF, predict the ICG metabolic pattern equation, and correlate it with postoperative visual acuity and peripapillary retinal nerve fiber layer thickness. Results: A total of 64 patients (64 eyes) were included, with an average age of 64.6±8.4 years, including 25 males (39.1%) and 39 females (60.9%). Preoperative NIR-FF images showed no ICG strong fluorescence. At 1 week postoperatively, diffuse ICG strong fluorescence appeared in the posterior pole, and the internal limiting membrane removal area exhibited a ring-like weak fluorescence. Over time, ICG strong fluorescence was observed along the vascular arch and nerve fiber trajectory, gradually diminishing toward the optic disc, with residual ICG fluorescence still visible at the optic disc at 1 year. The Python-based ICG fluorescence area detection system effectively measured intraocular residual ICG area. A predictive equation for the 12-month residual ICG area was constructed through linear regression analysis (Residual ICG area=0.22 × Residual ICG area at 6 months, R2=16%, P=0.002). Except for a negative correlation between the ICG residual area at 1 month and postoperative visual acuity (P=0.017, r=-0.195), no correlation was found between intraocular ICG fluorescence residual area and postoperative visual acuity or peripapillary retinal nerve fiber layer thickness at other follow-up times (all P>0.05). Conclusions: In patients with idiopathic epiretinal membrane undergoing ICG staining for internal limiting membrane peeling, ICG exhibits characteristic metabolic processes in the eye, with strong fluorescence along the vascular arch and nerve fiber trajectory, gradually converging toward the optic disc over time. The Python-based ICG fluorescence area detection system provides a clear display of the intraocular distribution characteristics of ICG after epiretinal membrane peeling and serves as a tool for predicting the metabolic patterns of ICG in the eye.

Protective Effects of Aspirin Supplemented With Quercetin in L-NAME-Induced Preeclampsia-Like Rats

Aspirin supplemented with quercetin was reported to enhance the therapeutic effects of aspirin in a rat model of preeclampsia. In this study, the underlying mechanisms were further explored. Preeclampsia was induced by L-NAME (50 mg/kg/day) via oral gavage from gestation day (GD)14 to GD19. Aspirin (1.5 mg/kg/day) administration was performed using aspirin mixed with rodent dough from GD0 to GD19. The administration of quercetin (2 mg/kg/day) was performed by intraperitoneal infusion from GD0 to GD19. Protein levels were evaluated using ELISA or Western blot, and microRNA (miRNA) level was evaluated by RT-PCR. Aspirin supplemented with quercetin ameliorated the increase of systolic blood pressure (SBP), proteinuria, tumor necrosis factor-alpha (TNF-alpha) and interleukin-6 (IL-6) levels, and improved the pregnancy outcomes in preeclampsia rats. Aspirin supplemented with quercetin inhibited miR-155 expression in preeclampsia rats. The decreased miR-155 level in placenta further increased the protein level of SOCS1 and inhibited the phosphorylation of p65. In this study, we demonstrated that aspirin supplemented with quercetin enhanced the effects of aspirin for the treatment of preeclampsia.

[Reflections on the inner limiting membrane peeling and its derivatives in macular hole surgery]

Internal limiting membrane (ILM) peeling is a critical step in the process of macular hole surgery, giving rise to various modified techniques such as ILM flip-over coverage, ILM and other tissue tamponade procedures, and foveal-sparing ILM peeling. All these approaches aim to improve the postoperative closure rate of macular holes. The goal of macular hole surgery is to better preserve the integrity of the foveal center structure, with the aim of achieving functional recovery on the basis of anatomical restoration. However, in clinical practice, there is a tendency to excessively choose certain surgical methods solely to pursue the closure rate of the hole, which may not be beneficial for the visual function recovery of the patients. This article discusses how to correctly select the internal limiting membrane and its derivative procedures in macular hole surgery, combining clinical practice and relevant domestic and international research literature. It aims to provide insights for colleagues performing macular hole surgery as a reference regarding this clinical focus issue.

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.