Lifetime adversity predicts depression, anxiety, and cognitive impairment in a nationally representative sample of older adults in the United States

OBJECTIVE

Although life stress and adversity are well-known risk factors for mental health problems and cognitive impairment among older adults, limited research has comprehensively examined the impact of both childhood and adulthood adversity on psychiatric and cognitive impairment symptoms over a prolonged period. To address this issue, we investigated how lifetime adversity exposure is related to symptoms of depression, anxiety, and cognitive impairment in a nationally representative, longitudinal sample of older adults in the United States.

METHOD

We analyzed data from the Health and Retirement Study (1992-2016). The sample included 3496 individuals (59.9% female), aged ≥64 years old (Mage = 76.0 ± 7.6 years in 2016). We used the individual-level panel data and ordinary least squares regressions to estimate associations between childhood and adulthood adversities, and later-life depression, anxiety, and cognitive impairment.

RESULTS

Many participants experienced a significant early life (38%) or adulthood (79%) stressor. Moreover, experiencing one childhood adversity (vs. none) was associated with a 17.4% increased risk of adulthood adversity. Finally, as hypothesized, childhood adversity exposure was related to experiencing more depression and anxiety symptoms in later life, whereas adulthood stressor exposure predicted more cognitive impairment as well as more depression and anxiety symptoms.

DISCUSSION

These findings demonstrate significant associations between lifetime adversity and symptoms of depression, anxiety, and cognitive impairment in older adults. Screening for lifetime stressors may thus help healthcare professionals and policymakers identify individuals who could potentially benefit from interventions designed to reduce stress and enhance resilience.

Cumulative Genetic Scores Interact with Maternal and Paternal Parenting in Predicting Parent-Adolescent Cohesion and Conflict

Previous research concerning the interplay between genetics and parenting in the development of the parent-child relationship during adolescence has been extremely scarce, predominantly adopting single-gene designs. This limited body of work has largely overlooked the distinct effects of maternal and paternal roles, as well as potential gender differences. Additionally, existing gene-by-environment (G × E) studies have mainly concentrated on adverse environmental factors and associated negative outcomes, somewhat neglecting positive environments and outcomes. The present study examined the interactions of cumulative genetic scores (CGS, dopamine receptor D2 TaqIA and oxytocin receptor gene rs53576 polymorphisms) with both positive and negative parenting on parent-adolescent cohesion and conflict. Furthermore, this study aimed to ascertain with which gene-environment model the potential G × E interactions would align. A total of 745 Chinese Han adolescents (Mage = 13.36 ± 0.96 years; 46.8% girls) from grades 7 to 9 participated in this study. Results revealed a significant effect of CGS and negative maternal parenting on mother-adolescent conflict among males, consistent with the weak differential susceptibility model. As CGS increased, the effects of negative maternal parenting on mother-son conflict were magnified. These findings have implications for the timing and focus of interventions aimed at improving parent-adolescent relationships.

CT venography combined with ultrasound-guided minimally invasive treatment for recurrent varicose veins: a pilot paired-design clinical trial

AIM

To compare 1-year outcomes of computed tomography venography (CTV) combined with ultrasound-guided minimally invasive treatment with ascending phlebography and ultrasound-guided treatment for recurrent varicose veins.

MATERIALS AND METHODS

Consecutive patients with unilateral recurrent varicose veins were matched by gender, age, C classification, and degree of obesity, and randomised in a 1:1 ratio to receive either CTV (CTV group) or ascending phlebography (control group) combined with ultrasound-guided minimally invasive treatment. Patients were followed up by clinical and ultrasound examination. Follow-up was scheduled at 1 week, and 3, 6, and 12 months. The primary outcome measure was the Venous Clinical Severity Score (VCSS) at 12 months. Measures of secondary outcome included Chronic Insufficiency Venous International Questionnaire-20 (CIVIQ-20) score, recurrence of varicose vein or ulcer during 12 months, ulcer healing time, detection and location of treated veins.

RESULTS

Eighty patients were enrolled. Median VCSS in the CTV group was lower than it in the control group (p=0.04) and the CIVIQ-20 score was higher than the control group (p=0.02). By 12 months, no symptomatically recurrent varicose veins or ulcers had occurred. The ulcer healing time in CTV group was shorter (p<0.01). A greater number of patients had treated veins detected using CTV than by ascending venography (p=0.01), especially among patients with recurrence reflux veins in the groin, perineum, and vulva (p<0.01).

CONCLUSION

CTV combined with ultrasound may be more helpful than ascending phlebography combined with ultrasound to improve treatment efficacy for recurrent varices. These results should be verified by an future study with more patients and long-term follow-up.

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.

Moral Dilemmas Regarding Physical Restraints in Intensive Care Units: Understanding Autonomy, Beneficence, Non-Maleficence and Justice in the Use of Physical Restraints

In intensive care units, patients are often restrained to ensure their safety, with physical restraints being the most commonly used method. However, physical restraints compromises the patient's freedom, health and comfort, and nurses often face moral dilemmas when deciding whether to use physical restraints. This article examines physical restraints through the four universal principles of autonomy, beneficence, non-maleficence and justice. Through these principles, the authors will critically explore whether the physical restraints of patients by nurses is ethical in practice and what moral issues exist. This paper also explores conflicts and moral dilemmas for nurses in this context. Finally, suggestions are made on changes to education and clinical practice.

Improving chilling tolerance of peanut seedlings by enhancing antioxidant-modulated ROS scavenging ability, alleviating photosynthetic inhibition, and mobilizing nutrient absorption

Peanut production is threatened by climate change. Damage to seedlings from low temperatures in early spring can limit yield. Plant adaptations to chilling stress remain unclear in peanut seedlings. It is essential to understand how peanut acquires chilling tolerance. We evaluated effects of chilling stress on growth and recovery of peanut seedlings. We compared and analysed biological characteristics, antioxidants, photosynthesis, biochemical and physiological responses, and nutrient absorption at varying levels of chilling. Compared with chilling-sensitive FH18, the reduced impact of chilling stress on chilling-tolerant NH5 was associated with reduced ROS accumulation, higher ascorbate peroxidase activity and soluble sugar content, lower soluble protein content, and smaller reductions in nutrient content during stress. After removal of chilling stress, FH18 had significant accumulation of O2 •- and H2O2, which decreased photosynthesis, nutrient absorption, and transport. ROS-scavenging reduced damage from chilling stress, allowed remobilization of nutrients, improved chilling tolerance, and restored plant functioning after chilling stress removal. These findings provide a reference for targeted research on peanut seedling tolerance to chilling and lay the foundation for bioinformatics-based research on peanut chilling tolerance mechanisms.

Pancreatic β-cell failure, clinical implications, and therapeutic strategies in type 2 diabetes

ABSTRACT

Pancreatic β-cell failure due to a reduction in function and mass has been defined as a primary contributor to the progression of type 2 diabetes (T2D). Reserving insulin-producing β-cells and hence restoring insulin production are gaining attention in translational diabetes research, and β-cell replenishment has been the main focus for diabetes treatment. Significant findings in β-cell proliferation, transdifferentiation, pluripotent stem cell differentiation, and associated small molecules have served as promising strategies to regenerate β-cells. In this review, we summarize current knowledge on the mechanisms implicated in β-cell dynamic processes under physiological and diabetic conditions, in which genetic factors, age-related alterations, metabolic stresses, and compromised identity are critical factors contributing to β-cell failure in T2D. The article also focuses on recent advances in therapeutic strategies for diabetes treatment by promoting β-cell proliferation, inducing non-β-cell transdifferentiation, and reprograming stem cell differentiation. Although a significant challenge remains for each of these strategies, the recognition of the mechanisms responsible for β-cell development and mature endocrine cell plasticity and remarkable advances in the generation of exogenous β-cells from stem cells and single-cell studies pave the way for developing potential approaches to cure diabetes.

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.

[Surgical treatment and prognosis analysis of hilar cholangiocarcinoma]

Objective: To investigate the surgical treatment effect and prognostic factors of hilar cholangiocarcinoma. Methods: This is an ambispective cohort study. From August 2005 to December 2022,data of 510 patients who diagnosed with hilar cholangiocarcinoma and underwent surgical resection at the Hepatobiliary Center of the First Affiliated Hospital of Nanjing Medical University were retrospectively collected. In the cohort,there were 324 males and 186 females,with an age of (M (IQR)) 63(13)years (range:25 to 85 years). The liver function at admission was Child-Pugh A (343 cases,67.3%) and Child-Pugh B (167 cases,32.7%). Three hundred and seventy-two(72.9%) patients had jaundice symptoms and the median total bilirubin was 126.3(197.6) μmol/L(range: 5.4 to 722.8 μmol/L) at admission. Two hundred and fourty-seven cases (48.4%) were treated with percutaneous transhepatic cholangial drainage or endoscopic nasobiliary drainage before operation. The median bilirubin level in the drainage group decreased from 186.4 μmol/L to 85.5 μmol/L before operation. Multivariate Logistic regression was used to identify the influencing factors for R0 resection,and Cox regression was used to construct multivariate prediction models for overall survival(OS) and disease-free survival(DFS). Results: Among 510 patients who underwent surgical resection,Bismuth-Corlett type Ⅲ-Ⅳ patients accounted for 71.8%,among which 86.1% (315/366) underwent hemi-hepatectomy,while 81.9% (118/144) underwent extrahepatic biliary duct resection alone in Bismuch-Corlett type Ⅰ-Ⅱ patients. The median OS time was 22.8 months, and the OS rates at 1-,3-,5-and 10-year were 72.2%,35.6%,24.8% and 11.0%,respectively. The median DFS time was 15.2 months,and the DFS rates was 66.0%,32.4%,20.9% and 11.0%,respectively. The R0 resection rate was 64.5% (329/510), and the OS rates of patients with R0 resection at 1-,3-,5-and 10-year were 82.5%, 48.6%, 34.4%, 15.2%,respectively. The morbidity of Clavien-Dindo grade Ⅲ-Ⅴ complications was 26.1%(133/510) and the 30-day mortality was 4.3% (22/510). Multivariate Logistic regression indicated that Bismuth-Corlett type Ⅰ-Ⅲ (P=0.009), hemi-hepatectomy and extended resection (P=0.001),T1 and T2 patients without vascular invasion (T2 vs. T1:OR=1.43 (0.61-3.35),P=0.413;T3 vs. T1:OR=2.57 (1.03-6.41), P=0.010;T4 vs. T1, OR=3.77 (1.37-10.38), P<0.01) were more likely to obtain R0 resection. Preoperative bilirubin,Child-Pugh grade,tumor size,surgical margin,T stage,N stage,nerve infiltration and Edmondson grade were independent prognostic factors for OS and DFS of hilar cholangiocarcinoma patients without distant metastasis. Conclusions: Radical surgical resection is necessary to prolong the long-term survival of hilar cholangiocarcinoma patients. Hemi-hepatectomy and extended resection,regional lymph node dissection and combined vascular resection if necessary,can improve R0 resection rate.

Analytical challenges in omics research on asthma and allergy: A National Institute of Allergy and Infectious Diseases workshop

Studies of asthma and allergy are generating increasing volumes of omics data for analysis and interpretation. The National Institute of Allergy and Infectious Diseases (NIAID) assembled a workshop comprising investigators studying asthma and allergic diseases using omics approaches, omics investigators from outside the field, and NIAID medical and scientific officers to discuss the following areas in asthma and allergy research: genomics, epigenomics, transcriptomics, microbiomics, metabolomics, proteomics, lipidomics, integrative omics, systems biology, and causal inference. Current states of the art, present challenges, novel and emerging strategies, and priorities for progress were presented and discussed for each area. This workshop report summarizes the major points and conclusions from this NIAID workshop. As a group, the investigators underscored the imperatives for rigorous analytic frameworks, integration of different omics data types, cross-disciplinary interaction, strategies for overcoming current limitations, and the overarching goal to improve scientific understanding and care of asthma and allergic diseases.

Associations of Breathing Pattern Disorder and Nijmegen Score With Clinical Outcomes in Difficult-to-Treat Asthma

BACKGROUND

Breathing pattern disorder (BPD) reflects altered biomechanical patterns of breathing that drive breathing difficulty and commonly accompanies difficult-to-treat asthma. Diagnosis of BPD has no gold standard, but Nijmegen Questionnaire (NQ) >23 is commonly used.

OBJECTIVES

We sought to advance clinical characterization of BPD and better understand the clinical utility of NQ in difficult asthma in patients from the Wessex AsThma CoHort of difficult asthma (WATCH) study.

METHODS

Associations between demographic and clinical factors in difficult asthma and BPD, ascertained by clinical diagnosis (yes/no, n = 476), by NQ scores (≤23: normal [no suggestion of BPD] and >23: abnormal [suggested BPD], n = 372), as well as the continuous raw NQ scores were assessed in univariate models to identify significant risk factors associated with the 3 BPD outcomes. For the clinician-diagnosed and NQ-based BPD, associations of continuous factors were assessed using the independent samples t test or the Mann-Whitney U test as appropriate for the data distribution or by the Spearman correlation test. Dichotomous associations were evaluated using χ2 tests. Multivariable logistic (dichotomous outcomes) and linear regression models (continuous outcomes) were developed to identify predictive factors associated with clinician-diagnosed and NQ-based BPD, dichotomous and continuous. Patients with data on NQ scores were grouped into NQ quartiles (low, moderate, high, and very high). The patterns of association of the quartiles with 4 health-related questionnaire outcomes were assessed using linear regression analyses.

RESULTS

Multivariable regression identified that clinically diagnosed BPD was associated with female sex (odds ratio [OR]: 1.85; 95% confidence interval [CI]: 1.07, 3.20), comorbidities (rhinitis [OR: 2.46; 95% CI: 1.45, 4.17], gastroesophageal reflux disease [GORD] [OR: 2.77; 95% CI: 1.58, 4.84], inducible laryngeal obstruction [OR: 4.37; 95% CI: 2.01, 9.50], and any psychological comorbidity [OR: 1.86; 95% CI: 1.13, 3.07]), and health care usage (exacerbations [OR: 1.07; 95% CI: 1.003, 1.14] and previous intensive care unit (ICU) admissions [OR: 2.03; 95% CI: 1.18, 3.47]). Abnormal NQ-based BPD diagnosis was associated with history of eczema (OR: 1.83; 95% CI: 1.07, 3.14), GORD (OR: 1.94; 95% CI: 1.15, 3.27), or any psychological comorbidity (OR: 4.29; 95% CI: 2.64, 6.95) at multivariable regression. Differences between clinical and NQ-based BPD traits were also found with 42% discordance in BPD state between these definitions. Multivariable linear regression analysis with NQ as a continuous outcome showed positive association with worse asthma outcomes (admission to ICU, P = .037), different phenotypic traits (female sex, P = .001; ever smoker, P = .025), and greater multimorbidity (GORD, P = .002; sleep apnea, P = .04; and any psychological comorbidity, P < .0001).

CONCLUSION

BPD is associated with worse health outcomes and negative health impacts in difficult asthma within a multimorbidity disease model. It therefore merits better recognition and prompt treatment. Clinical diagnosis and NQ offer different perspectives on BPD, so this goal may be best addressed by considering clinical features alongside the magnitude of NQ.

Evaluation of Safety and Efficacy of Amniotic Mesenchymal Stem Cells for POI in Animals

The efficacy of human amniotic mesenchymal stem cell (hAMSC) ovarian injection in improving ovarian function in primary ovarian insufficiency (POI) patients has been shown in some reports. However, the safety and efficacy of hAMSC vein injection remains unclear. In this study, we evaluated the safety and efficacy of hAMSC intravenous injection in cynomolgus macaques and SD rats and provided evidence for clinical trials. The hAMSCs were transplanted three times in SD rats at low, medium, and high doses. The animal behavior and biochemical and biophysical parameters were routinely monitored on a 2-month period posttransplantation, and histopathologic examinations were also performed. Experiments on the acute toxicity, allergy test, and hemolysis test showed that hAMSCs possess good biocompatibility. Our results showed that the maximum tolerated dose of hAMSCs in SD rats was 4.0 × 107 cells/kg. The maximum safe dose with three injections of hAMSCs in SD rats was 5.0 × 106 cells/kg. In addition, the results demonstrated that hAMSCs may restore POI rat ovarian function after two injections of 2.5 × 106 cells/kg or 5.0 × 106 cells/kg, which improved the disturbed estrous cycle, hormone levels, and ovarian lesions induced by pZP3. In conclusion, the preclinical results suggested that the transplantation of hAMSCs may be safe and efficacious for SD rats at doses of 5.0 × 106 cells/kg and lower.

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

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

Feasibility study of the multishot gradient-echo planar imaging sequence in non-enhanced and free-breathing whole-heart magnetic resonance coronary angiography

AIM

To investigate the feasibility of non-enhanced and free-breathing whole-heart magnetic resonance coronary angiography (MRCA) using multishot gradient-echo planar imaging (MSG-EPI).

MATERIALS AND METHODS

In total, 29 healthy volunteers were recruited for free-breathing whole-heart MRCA acquisition using the MSG-EPI sequence and fast gradient echo (GRE) sequence. After the examination, the actual scanning times, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) of the left main (LM) coronary artery, subjective quality scores for each segment, and evaluable length of the coronary artery were recorded and statistically analysed.

RESULTS

There was no significant difference between the SNRLM of the MSG-EPI sequence and fast GRE sequence (p=0.130), but the CNRLM of the MSG-EPI sequence was higher (p=0.001). The subjective quality score of the mid- and distal left anterior descending branch as well as the distal circumflex branch of the coronary artery in the MSG-EPI sequence was higher than that in the fast GRE sequence (p=0.003, 0.001, and 0.003, respectively). The evaluable length of the left anterior descending branch and the circumflex branch was better using the MSG-EPI sequence than that of the fast GRE sequence (p=0.015 and < 0.001, respectively). Moreover, the scanning time of the MSG-EPI sequence was 54.5% less than that of the fast GRE sequence (p<0.001).

CONCLUSION

The MSG-EPI sequence improves the subjective and objective image quality of MRCA as well as reduces the scanning time.

MRI-based Multiregional Radiomics for Pretreatment Prediction of Distant Metastasis After Neoadjuvant Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer

RATIONALE AND OBJECTIVES

To develop and validate a nomogram based on intratumoral and peritumoral radiomics signatures for pretreatment prediction of distant metastasis-free survival (DMFS) in patients after neoadjuvant chemoradiotherapy (NCRT) with locally advanced rectal cancer (LARC).

MATERIALS AND METHODS

This retrospective study included 230 patients (161 training cohort; 69 validation cohort) with LARC who underwent NCRT and surgery. Radiomics features were extracted on T2-weighted images from gross tumor volume (GTV) and volumes of 4-mm, 6-mm, and 8-mm peritumoral regions (PTV4, PTV6, and PTV8). The least absolute shrinkage and selection operator (LASSO)-Cox analysis were used for features selection and models construction. The performance of each model in predicting DMFS was evaluated by the Concordance index (C-index) and time-independent receiver operating characteristic curve (ROC).

RESULTS

The PTV4 radiomics model demonstrated superior performance compared to the PTV6 and PTV8 radiomics models, with C-indexes of 0.750 and 0.703 in the training and validation cohorts, respectively. The nomogram was constructed by integrating the GTV radiomics signature, PTV4 radiomics signature, and relevant clinical characteristics, including CA19-9 level, clinical T stage, and clinical N stage. The nomogram achieved C-indexes of 0.831 and 0.748, with corresponding AUCs of 0.872 and 0.808 for 5-year DMFS in the training and validation cohorts, respectively. Kaplan-Meier analysis revealed that a cut-off value of 1.653 effectively stratified patients into high- and low-risk groups for DM (P < 0.001).

CONCLUSION

The intra-peritumoral radiomics nomogram is a favorable tool for clinicians to develop personalized systemic treatment and intensive follow-up strategies to improve patient prognosis.

Integrating multi-index determination coupled with hierarchical cluster analysis to evaluate the quality consistency of PVE30, an anti-HSV "glycoprotein" macromolecule of Prunellae Spica

INTRODUCTION

Prunellae Spica (PS), derived from the dried fruit spikes of Prunella vulgaris L., is a traditional Chinese medicinal herb. Our previous studies found that PVE30, a water-extracting ethanol-precipitating "glycoprotein" macromolecule of PS, was a potential anti-herpes simplex virus (HSV) candidate. However, due to the complex structure and diverse bioactivity of the "glycoprotein", ensuring its quality consistency across different batches of PVE30 becomes particularly challenging. This poses a significant hurdle for new drug development based on PVE30.

OBJECTIVE

Our study aimed to integrate multi-index determination coupled with hierarchical cluster analysis (HCA) to holistically profile the quality consistency of "glycoprotein" in PVE30.

METHODS

High-performance gel permeation chromatography with refractive index detector (HPGPC-RID) was used to characterise the molecular weight (Mw) distribution, HPLC-PDA was used to quantitatively analyse the composed monosaccharides and amino acids, and UV-VIS was used to quantify the contents of polysaccharides and proteins. Qualitative and quantitative consistency was analysed for each single index in 16 batches of PVE30, and a 16 × 38 data matrix, coupled with HCA, was used to evaluate the holistic quality consistency of PVE30.

RESULTS

The newly developed and validated methods were exclusive, linear, precise, accurate, and stable enough to quantify multi-indexes in PVE30. Single-index analysis revealed that 16 batches of PVE30 were qualitatively consistent in Mw distribution, polysaccharides and proteins, and the composition of composed monosaccharides and amino acids but quantitatively inconsistent in the relative contents of some "glycoprotein" macromolecules, as well as the composed monosaccharides/amino acids. HCA showed that the holistic quality of PVE30 was inconsistent, the inconsistency was uncorrelated with the regions where PS was commercially collected, and the contents of 17 amino acids and 2 monosaccharides contributed most to the holistic quality inconsistency.

CONCLUSION

Multi-index determination coupled with HCA was successful in evaluating the quality consistency of PVE30, and the significant difference in quantitative indices was not caused by the origin of PS. The cultivating basis should be confirmed for PVE30-based new drug development.

Defect Engineering of 2D Semiconductors for Dual Control of Emission and Carrier Polarity

2D transition metal dichalcogenides (TMDCs) are considered as promising materials in post-Moore technology. However, the low photoluminescence quantum yields (PLQY) and single carrier polarity due to the inevitable defects during material preparation are great obstacles to their practical applications. Here, an extraordinary defect engineering strategy is reported based on first-principles calculations and realize it experimentally on WS2 monolayers by doping with IIIA atoms. The doped samples with large sizes possess both giant PLQY enhancement and effective carrier polarity modulation. Surprisingly, the high PL emission maintained even after one year under ambient environment. Moreover, the constructed p-n homojunctions shows high rectification ratio (≈2200), ultrafast response times and excellent stability. Meanwhile, the doping strategy is universally applicable to other TMDCs and dopants. This smart defect engineering strategy not only provides a general scheme to eliminate the negative influence of defects, but also utilize them to achieve desired optoelectronic properties for multifunctional applications.

Whipple's disease of the respiratory system: A case report

Whipple's disease (WD) is a multiple-system chronic disease caused by Tropheryma whipplei (T. whipplei) infection. The present study describes 3 cases of WD with clinical manifestations of cough, chest pain, headache, dyspnea, sputum, joint pain, abdominal pain, diarrhea and weight loss. Chest computed tomography (CT) showed signs of plaques, nodules and pleural thickening; and bronchoscopic alveolar lavage fluid metagenomic-sequencing indicated that it was T. whipplei. One patient was treated with meropenem as the starting regimen and two patients were treated with ceftriaxone as the starting regimen. Furthermore, two patients were provided with a maintenance regimen of cotrimoxazole and one was given a maintenance regimen of minocycline, which was combined with meropenem and ceftriaxone in order to improve their cough, chest pain, headache and dyspnea symptoms. To the best of our knowledge, there are few reports on WD of the respiratory system caused by T. whipplei, and differential diagnosis is the key to clinical diagnosis. When WD of the respiratory system is difficult to diagnose, metagenomic second-generation sequencing (mNGS) may be a better choice, which can achieve early diagnosis and early treatment. However, its clinical value is still limited; therefore, more research needs to be conducted in the future.

Integration of metabolomics and network pharmacology technology to explain the effect mechanisms of Danggui Buxue decoction in vascular dementia

Danggui Buxue decoction (DBD) is a traditional Chinese medicine herbal decoction that has a good therapeutic effect on vascular dementia (VaD). However, its pharmacodynamic substances and underlying mechanisms are ambiguous. The work aimed to decipher the pharmacodynamic substances and molecular mechanisms of DBD against VaD rats based on gas chromatography-mass spectrometry metabonomics, network pharmacology, molecular docking, and experimental verification. The results indicated that DBD significantly improved the learning abilities and cognitive impairment in the VaD rat model. Integration analysis of the metabolomics and network pharmacology approach revealed that DBD might primarily affect arachidonic acid (AA) and inositol phosphate metabolic pathways by regulating the platelet activation signaling pathways. Six core targets (TNF [tumor necrosis factor], IL-6 [interleukin 6], PTGS2 [prostaglandin-endoperoxide synthase 2], MAPK1, MAPK3, and TP53) in the platelet activation signaling pathways also had a good affinity to seven main active components (saponins, organic acids, flavonoids, and phthalides) of DBD through the verification of molecular docking. Enzyme-linked immunosorbent assay results (ELISA) showed that the levels of TNF, IL-6, PTGS2, thromboxane B2, and caspase-3 in the platelet activation signaling pathway can be regulated by DBD. Our results indicated that DBD treated VaD mainly by modulating the platelet activation signaling pathway, and AA and inositol phosphate metabolism.

Effects of soyhulls with different particle size on the growth performance, blood indices and gut microbiota of yellow feather broilers

1. The objective of this study was to determine the effects of soyhulls with different particle sizes on the growth performance, blood indices and gut microbiota of yellow feather broilers.2. Total of 240 healthy, one-day-old, yellow feather broilers were randomly divided into four groups, with six pen replicates within each group and ten birds per pen. The control group birds were fed the basal diet (Control). For the treatment groups, 5% soyhulls with different particle sizes were included in the basal diet. The particle size geometric mean diameters (dgw) of the soyhulls in the three treatment groups were 299.69 μm (LowPS), 489.85 μm (MediumPS) and 734.83 μm (HighPS) with geometric standard deviation (Sgw) 1.75 μm, 1.62 μm and 1.67 μm, respectively.3. Results showed that the growth performance variables and organ indices were not different among the four groups. The MediumPS group had increased TG, T-CHO, ALT, HDL-C, and GSH-PX levels and decreased T-AOC levels, whereas LowPS and HighPS groups had increased HDL-C and GSH-PX levels (p < 0.05). Microbial diversity analysis showed that the intestinal microbiota of yellow feather broilers mainly included Firmicutes and Bacteroidetes. Inclusion of 5% soyhulls with different particle size had no effect on alpha diversity indices of caecal microbiota. The HighPS group had significantly higher relative abundance of Firmicutes spp. and lower Bacteroidetes spp. compared with the LowPS and MediumPS group but this was not different from the Control group. The relative abundance of Cyanobacteria spp. was significantly higher in the HighPS group than the other three groups. LEfSe analysis showed that there were more enriched biomarker taxa in the groups with soyhulls than the control group.4. Overall, the inclusion of soyhulls with different particle sizes had limited effects on growth performance, blood indices and caecal microbiota composition of yellow feather broilers.

Sugar-coated bullets: Unveiling the enigmatic mystery 'sweet arsenal' in osteoarthritis

Glycosylation is a crucial post-translational modification process where sugar molecules (glycans) are covalently linked to proteins, lipids, or other biomolecules. In this highly regulated and complex process, a series of enzymes are involved in adding, modifying, or removing sugar residues. This process plays a pivotal role in various biological functions, influencing the structure, stability, and functionality of the modified molecules. Glycosylation is essential in numerous biological processes, including cell adhesion, signal transduction, immune response, and biomolecular recognition. Dysregulation of glycosylation is associated with various diseases. Glycation, a post-translational modification characterized by the non-enzymatic attachment of sugar molecules to proteins, has also emerged as a crucial factor in various diseases. This review comprehensively explores the multifaceted role of glycation in disease pathogenesis, with a specific focus on its implications in osteoarthritis (OA). Glycosylation and glycation alterations wield a profound influence on OA pathogenesis, intertwining with disease onset and progression. Diverse studies underscore the multifaceted role of aberrant glycosylation in OA, particularly emphasizing its intricate relationship with joint tissue degradation and inflammatory cascades. Distinct glycosylation patterns, including N-glycans and O-glycans, showcase correlations with inflammatory cytokines, matrix metalloproteinases, and cellular senescence pathways, amplifying the degenerative processes within cartilage. Furthermore, the impact of advanced glycation end-products (AGEs) formation in OA pathophysiology unveils critical insights into glycosylation-driven chondrocyte behavior and extracellular matrix remodeling. These findings illuminate potential therapeutic targets and diagnostic markers, signaling a promising avenue for targeted interventions in OA management. In this comprehensive review, we aim to thoroughly examine the significant impact of glycosylation or AGEs in OA and explore its varied effects on other related conditions, such as liver-related diseases, immune system disorders, and cancers, among others. By emphasizing glycosylation's role beyond OA and its implications in other diseases, we uncover insights that extend beyond the immediate focus on OA, potentially revealing novel perspectives for diagnosing and treating OA.

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

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

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

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

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Affiliation(s)

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

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

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

[Application value of laparoscopic double stapler firings and double stapling technique combined with rectal eversion and total extra-abdominal resection in the sphincter-preserving resection of low rectal cancer]

Objectives: To investigate the application value of laparoscopic double stapler firings and double stapling technique combined with rectal eversion and total extra-abdominal resection (LDER) in the anal preservation treatment of low rectal cancer. Methods: Inclusion criteria: (1) age was 18-70; (2) the distance of the lower tumor edge from the anal verge was 4-5 cm; (3) primary tumor with a diameter ≤3 cm; (4) preoperative staging of T1~2N1~2M0; (5) "difficult pelvis", defined as ischial tuberosity diameter<10 cm or body mass index>25 kg/m2; (6) patients with strong intention for sphincter preservation; (7) no preoperative treatment (e.g., chemotherapy, radiotherapy, molecular targeted therapy, or immunotherapy); (8) no lateral lymph node enlargement; (9) no previous anorectal surgery; (10) patients with good basic condition who could tolerate surgery. Exclusion criteria: (1) previously suffered from malignant tumors of the digestive tract or currently suffering from malignant tumors out of the digestive tract; (2) patients with preoperative anal dysfunction (Wexner score ≥ 10), or fecal incontinence. The specific surgical steps are as follows: the distal end of the rectum was dissected to the level of the interspace between internal and external sphincters of anal canal. Five centimeters proximal to the tumor, the mesorectum was ligated, and a liner stapler was used to transect the rectum. The distal rectum with the tumor were then everted and extracted through the anus. The rectum was transected 0.5-1.0 cm distal to the tumor with a linear stapler. Full thickness suture was used to reinforce the stump of the rectum, which was then brought back into the pelvic cavity. Finally, an end-to-end anastomosis between the colon and the rectum was performed. A retrospective descriptive study was performed of the clinical and pathological data of 12 patients with T1-T2 stage low rectal cancer treated with LDER at Henan Provincial People's Hospital from January 2020 to December 2022. Results: All 12 patients successfully completed LDER with sphincter preservation, without conversion to open surgery or changes in surgical approach. The median surgical time was 272 (155-320) minutes, with a median bleeding volume of 100 (50-200) mL. No protective stoma was performed, and all patients received R0 resection. The average hospital stay was 9 (7-15) days. There were no postoperative anastomotic leakage or perioperative deaths. All 12 patients received postoperative follow-up, with a median follow-up of 12 months (6-36 months) and a Wexner score of 8 (5-14) at 6 months postoperatively. There was no tumor recurrence or metastasis during the follow-up period. Conclusions: LDER is safe and effective for the treatment of low rectal cancer.

Insulin and glycolysis dependency of cardioprotection by nicotinamide riboside

Decreased nicotinamide adenine dinucleotide (NAD+) levels contribute to various pathologies such as ageing, diabetes, heart failure and ischemia-reperfusion injury (IRI). Nicotinamide riboside (NR) has emerged as a promising therapeutic NAD+ precursor due to efficient NAD+ elevation and was recently shown to be the only agent able to reduce cardiac IRI in models employing clinically relevant anesthesia. However, through which metabolic pathway(s) NR mediates IRI protection remains unknown. Furthermore, the influence of insulin, a known modulator of cardioprotective efficacy, on the protective effects of NR has not been investigated. Here, we used the isolated mouse heart allowing cardiac metabolic control to investigate: (1) whether NR can protect the isolated heart against IRI, (2) the metabolic pathways underlying NR-mediated protection, and (3) whether insulin abrogates NR protection. NR protection against cardiac IRI and effects on metabolic pathways employing metabolomics for determination of changes in metabolic intermediates, and 13C-glucose fluxomics for determination of metabolic pathway activities (glycolysis, pentose phosphate pathway (PPP) and mitochondrial/tricarboxylic acid cycle (TCA cycle) activities), were examined in isolated C57BL/6N mouse hearts perfused with either (a) glucose + fatty acids (FA) ("mild glycolysis group"), (b) lactate + pyruvate + FA ("no glycolysis group"), or (c) glucose + FA + insulin ("high glycolysis group"). NR increased cardiac NAD+ in all three metabolic groups. In glucose + FA perfused hearts, NR reduced IR injury, increased glycolytic intermediate phosphoenolpyruvate (PEP), TCA intermediate succinate and PPP intermediates ribose-5P (R5P) / sedoheptulose-7P (S7P), and was associated with activated glycolysis, without changes in TCA cycle or PPP activities. In the "no glycolysis" hearts, NR protection was lost, whereas NR still increased S7P. In the insulin hearts, glycolysis was largely accelerated, and NR protection abrogated. NR still increased PPP intermediates, with now high 13C-labeling of S7P, but NR was unable to increase metabolic pathway activities, including glycolysis. Protection by NR against IRI is only present in hearts with low glycolysis, and is associated with activation of glycolysis. When activation of glycolysis was prevented, through either examining "no glycolysis" hearts or "high glycolysis" hearts, NR protection was abolished. The data suggest that NR's acute cardioprotective effects are mediated through glycolysis activation and are lost in the presence of insulin because of already elevated glycolysis.

Multiple isotopes decipher the nitrogen cycle in the cascade reservoirs and downstream in the middle and lower Yellow River: Insight for reservoir drainage period

Intensive anthropogenic activities, such as excessive nitrogen input and dam construction, have altered the nitrogen cycle in the global river system. However, the focus on the source, transformation and fate of nitrogen in the Yellow River is still scarce. In this study, the multiple isotopes (δ15N-NO3-, δ18O-NO3-, δ15N-NH4+ and δ15N-PN) were deciphered to explore the nitrogen cycling processes and the driving factors in the thermally stratified cascade reservoirs (Sanmenxia Reservoir: SMXR and Xiaolangdi Reservoir: XLDR) and Lower Yellow River (LYR) during the drainage period of the XLDR. In the SMXR, algal bloom triggered the assimilation process in the upper layer before the SMX Dam, followed by remineralization and subsequent nitrification processes in the lower water layers. The nitrification reaction in the XLDR progressively increased along both longitudinal and vertical directions to the lower layer of the XLD Dam, which was linked to the variation in the water residence time of riverine, transition and lentic zones. The robust nitrification rates in the lower layer of the lentic zone coincided with the substantial depletion of nitrate isotopic composition and enrichment of both δ15N-PN and δ15N-NH4+, indicating the longer water residence time not only promoted the growth of the nitrifying population but also facilitated the remineralization to enhance NH4+ availability. In the LYR, the slight nitrate assimilation, as indicated by nitrate isotopic composition and fractionation models, was the predominant nitrogen transformation process. The Bayesian isotope mixing model results showed that manure and sewage was the dominant nitrate source (50 %) in the middle and lower Yellow River. Notably, the in-reservoir nitrification was a significant nitrate source (27 %) in the XLDR and LYR. Our study deepens the understanding of anthropogenic activities impacting the nitrogen cycle in the river-reservoir system, providing valuable insight into water quality management and nitrogen cycle mechanisms in the Yellow River.

Epigenetic Features in Newborns Associated with Preadolescence Lung Function and Asthma Acquisition during Adolescence

The association between newborn DNA methylation (DNAm) and asthma acquisition (AA) during adolescence has been suggested. Lung function (LF) has been shown to be associated with asthma risk and its severity. However, the role of LF in the associations between DNAm and AA is unclear, and it is also unknown whether the association between DNAm and AA is consistent with that between DNAm and LF. We address this question through assessing newborn epigenetic features of preadolescence LF and of AA during adolescence, along with their biological pathways and processes. Our study's primary medical significance lies in advancing the understanding of asthma's early life origins. By investigating epigenetic markers in newborns and their association with lung function in preadolescence, we aim to uncover potential early biomarkers of asthma risk. This could facilitate earlier detection and intervention strategies. Additionally, exploring biological pathways linking early lung function to later asthma development can offer insights into the disease's pathogenesis, potentially leading to novel therapeutic targets.

METHODS

The study was based on the Isle of Wight Birth cohort (IOWBC). Female subjects with DNAm data at birth and with no asthma at age 10 years were included (n = 249). The R package ttScreening was applied to identify CpGs potentially associated with AA from 10 to 18 years and with LF at age 10 (FEV1, FVC, and FEV1/FVC), respectively. Agreement in identified CpGs between AA and LF was examined, along with their biological pathways and processes via the R function gometh. We tested the findings in an independent cohort, the Avon Longitudinal Study of Parents and Children (ALSPAC), to examine overall replicability.

RESULTS

In IOWBC, 292 CpGs were detected with DNAm associated with AA and 1517 unique CpGs for LF (514 for FEV1, 436 for FVC, 408 for FEV1/FVC), with one overlapping CpG, cg23642632 (NCKAP1) between AA and LF. Among the IOWBC-identified CpGs, we further tested in ALSPAC and observed the highest agreement between the two cohorts in FVC with respect to the direction of association and statistical significance. Epigenetic enrichment analyses indicated non-specific connections in the biological pathways and processes between AA and LF.

CONCLUSIONS

The present study suggests that FEV1, FVC, and FEV1/FVC (as objective measures of LF) and AA (incidence of asthma) are likely to have their own specific epigenetic features and biological pathways at birth. More replications are desirable to fully understand the complexity between DNAm, lung function, and asthma acquisition.

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.

[Influences and mechanism of extracellular vesicles from dermal papilla cells of mice on human hypertrophic scar fibroblasts]

Objective: To investigate the influences and mechanism of extracellular vesicles from dermal papilla cells (DPC-EVs) of mice on human hypertrophic scar fibroblasts (HSFs). Methods: The study was an experimental research. The primary dermal papilla cells (DPCs) of whiskers were extracted from 10 6-week-old male C57BL/6J mice and identified successfully. The DPC-EVs were extracted from the 3rd to 5th passage DPCs by ultracentrifugation, and the morphology was observed through transmission electron microscope and the particle diameter was detected by nanoparticle tracking analyzer (n=3) at 24 h after culture. The 3rd passage of HSFs were divided into DPC-EV group and phosphate buffer solution (PBS) group, which were cultured with DPC-EVs and PBS, respectively. The cell scratch test was performed and cell migration rate at 24 h after scratching was calculated (n=5). The cell proliferation levels at 0 (after 12 h of starvation treatment and before adding DPC-EVs or PBS), 24, 48, 72, and 96 h after culture were detected by using cell counting kit 8 (n=4). The protein expressions of α-smooth muscle actin (α-SMA) and collagen typeⅠ (ColⅠ) in cells at 24 h after culture were detected by immunofluorescence method and Western blotting, and the protein expression of Krüppel-like factor 4 (KLF4) in cells at 24 h after culture was detected by Western blotting. After the 3rd passage of HSFs were cultured with DPC-EVs for 24 h, the cells were divided into blank control group, KLF4 knockdown group, and KLF4 overexpression group according to the random number table. The cells in blank control group were only routinely cultured for 48 h. The cells in KLF4 knockdown group and KLF4 overexpression group were incubated with KLF4 knockdown virus for 24 h, then the cells in KLF4 knockdown group were routinely cultured for 24 h while the cells in KLF4 overexpression group were incubated with KLF4 overexpression virus for 24 h. The protein expressions of KLF4, α-SMA, and ColⅠ in cells were detected by Western blotting at 48 h after culture. Results: At 24 h after culture, the extracted DPC-EVs showed vesicular structure with an average particle diameter of 108.8 nm. At 24 h after scratching, the migration rate of HSFs in PBS group was (54±10)%, which was significantly higher than (29±8)% in DPC-EV group (t=4.37, P<0.05). At 48, 72, and 96 h after culture, the proliferation levels of HSFs in DPC-EV group were significantly lower than those in PBS group (with t values of 4.06, 5.76, and 6.41, respectively, P<0.05). At 24 h after culture, the protein expressions of α-SMA and ColⅠ of HSFs in DPC-EV group were significantly lower than those in PBS group, while the protein expression of KLF4 was significantly higher than that in PBS group. At 48 h after culture, compared with those in blank control group, the protein expression of KLF4 of HSFs in KLF4 knockdown group was down-regulated, while the protein expressions of α-SMA and ColⅠ were both up-regulated; compared with those in KLF4 knockdown group, the protein expression of KLF4 of HSFs in KLF4 overexpression group was up-regulated, while the protein expressions of ColⅠ and α-SMA were down-regulated. Conclusions: The DPC-EVs of mice can inhibit the proliferation and migration of human HSFs and significantly inhibit the expressions of fibrosis markers α-SMA and ColⅠ in human HSFs by activating KLF4.

Diagnostic and prognostic value of parameters of erector spinae in patients with uremic sarcopenia

AIM

This study aimed to investigate whether computed tomography (CT)-measured erector spinae parameters (ESPs) have diagnostic, severity assessment, and prognostic predictive value in uremic sarcopenia (US).

MATERIALS AND METHODS

A total of 202 uremic patients were enrolled and divided into two groups: a control group and a sarcopenia group. Sarcopenia was classified into two types: severe and nonsevere. The area, volume, and density of the erector spinae (ES) were measured using chest CT images, and the relevant ESP, including the erector spinae index (ESI), total erector spinae volume (TESV), erector spinae density (ESD), and erector spinae gauge (ESG) were calculated. The occurrence of adverse events was followed-up for 36 months. The diagnostic value and severity of US were determined using the receiver operating characteristic (ROC) curve. Survival curves diagnosed using CT were plotted and compared with the curve drawn using the gold standard. Cox regression analysis was used to identify independent risk factors associated with survival in US.

RESULTS

With an area under the curve (AUC) of 0.840 and 0.739, the combined ESP has diagnostic value and the ability to assess the severity of US. There was no significant difference in the survival curve between the combined ESP for the diagnosis of US and the gold standard (P > 0.05). ESI is a standalone predictor of survival in patients with US.

CONCLUSION

ESP measured by CT has diagnostic values for US and its severity, as well as being a predictive value for the prognosis of US.

Intracardiac leakage of cement during artificial femoral head replacement: a case report and review

Bone cement leakage from the femoral medullary cavity is a rare complication following hip replacement. Currently, there are no reports of bone cement leakage into the heart. Here, we report an 81-year-old female patient with right femoral neck fracture. A thorough preoperative examination showed that bone cement had leaked into the heart during right femoral head replacement, leading to the death of the patient that night. Postoperative cardiac ultrasound showed that bone cement entered the vascular system through the femoral medullary cavity and subsequently entered the heart. Extreme deterioration in the patient's condition resulted in death that night. Unfortunately, the patient's family abandoned the idea of surgical removal of foreign bodies, leading to inevitable death. This case emphasizes the risk of clinical manifestations of cardiac embolism of bone cement after artificial femoral head replacement, suggesting that the risk of such embolism might be underestimated. We propose routine real-time C-arm X-ray guidance and injection of an appropriate amount of bone cement to prevent serious cardiopulmonary failure.

The impact of caregiver burden on quality of life in family caregivers of patients with advanced cancer: a moderated mediation analysis of the role of psychological distress and family resilience

BACKGROUND

The caregiver burden frequently experienced by family members tending to advanced cancer patients significantly impacts their psychological well-being and quality of life (QoL). Although family resilience might function as a mitigating factor in this relationship, its specific role remains to be elucidated. This study aims to probe the mediating effect of psychological distress on the relationship between caregiver burden and QoL, as well as the moderating effect of family resilience.

METHODS

A cross-sectional study was conducted between June 2020 and March 2021 in five tertiary hospitals in China. Data were collected on caregiver burden, family resilience, psychological distress (including anxiety and depression), and QoL. Moderated mediation analysis was performed.

RESULTS

Data analysis included 290 caregivers. It confirmed the mediating role of psychological distress in the caregiver burden-QoL relationship (P < 0.001). Both overall family resilience and the specific dimension of family communication and problem-solving (FCPS) demonstrated significant moderating effects on the "psychological distress/anxiety-QoL" paths (P < 0.05). The utilization of social and economic resources (USER) significantly moderated the association between depression and QoL (P < 0.05).

CONCLUSIONS

The study corroborates psychological distress's mediation between caregiver burden and QoL and family resilience's moderation between psychological distress and QoL. It underscores the need for minimizing psychological distress and bolstering family resilience among caregivers of advanced cancer patients. Accordingly, interventions should be tailored, inclusive of psychological assistance and promotion of family resilience, particularly focusing on FCPS and USER, to augment the caregivers' well-being and QoL.

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.

Mediating effect of psychological capital on the relationship between mental health literacy and coping styles among newly recruited nurses

BACKGROUND

Newly recruited nurses face multiple sources of stress and their coping styles need to be focused on to ensure good mental health. This study aimed to examine the relationship among mental health literacy, psychological capital and coping styles in newly recruited nurses.

METHODS

A cross-sectional study was conducted in August and September 2022. A total of 315 newly recruited nurses were recruited in a tertiary hospital in Henan Province, central China, employing the convenience sampling method. The self-reported questionnaires were sent through a QR code, including the Mental Health Literacy Scale for Healthcare Students, Psychological Capital Questionnaire, and Simplified Coping Style Questionnaire. Pearson correlation analysis was used to evaluate the relationships among the variables. Mediation analysis was performed to identify the mediating effect of psychological capital on the relationship between mental health literacy and coping styles.

RESULTS

Positive coping showed a positive relationship with psychological capital and mental health literacy, while negative coping showed a negative relationship with psychological capital and mental health literacy. For positive coping, psychological capital was a partial mediator with an effect of 0.140, accounting for 62.8%. For negative coping, a full mediating effect was shown by psychological capital between mental health literacy and negative coping, with an indirect effect of -0.048.

CONCLUSION

Psychological capital plays a partial and complete mediating role between mental health literacy and different coping styles among newly recruited nurses. Diversified training and personalized guidance in improving mental health literacy and increasing psychological capital simultaneously can be provided to newly recruited nurses continuously to adjust their coping styles.

The Implication of Diabetes-Specialized Nurses in Aiming for the Better Treatment and Management of Patients with Diabetes Mellitus: A Brief Narrative Review

Diabetes mellitus (DM) is regarded as one of the most critical public health challenges of the 21st century. It has evolved into a burgeoning epidemic since the last century, and today ranks among the major causes of mortality worldwide. Diabetes specialist nurses (DSNs) are central to good patient care and outcomes including confident self-care management. Evidence shows that DSNs are cost-effective, improve clinical outcomes, and reduce length of stay in hospital. In this brief narrative review, we aim to describe the roles of DSNs and their contribution in the treatment and management of patients with DM. This narrative review describes the importance of DSNs in healthcare practice, in the inpatient and outpatient departments, in the pediatrics department, in managing diabetic foot ulcers, in the treatment and management of gestational diabetes, in prescribing medications for DM and in diabetes self-management education on glycosylated hemoglobin, and cardiovascular risk factors. To conclude, DSNs have a crucial role in the treatment and management of patients with DM and its complications. DSNs have a great impact on diabetes therapy, and hence implementation of DSNs and nurse-led diabetic clinics might be beneficial for the health care system. Finally, having DSNs might significantly contribute to good healthcare practice and support. Even though DSNs are not available in several regions around the globe, and even though this post is still new to several health care institutions, the presence of DSNs recognized and certified by the various healthcare systems would be very useful.

[Injury death spectrum in children aged 0-14 years and its urban-rural difference in Tianjin, 1999-2021]

Objective: To analyze the characteristics, change of injury death spectrum in children aged 0-14 years and its urban-rural difference in Tianjin. Methods: The incidence data of injury death in children aged 0-14 years in Tianjin from 1999 to 2021 were collected from the "Population Based Mortality Surveillance System in Tianjin". We calculated constituent ratio, crude and standardized mortality rates in different subgroups of the population and major injury subtypes, and compared the rural-urban differences. The Cochran-Armitage trend test was used to analyze temporal trends in cause-of-death component ratios. Joinpoint regression model was used to calculate average annual percent change (AAPC). Seasonal difference in injury mortality risk were expressed as mortality ratio and 95% confidence interval. Results: From 1999 to 2021, injury was the third cause of death in children aged 0-14 years in Tianjin. The percentage of children who died in health-care facilities in rural area was 31.08%, which was lower than 37.82% in urban area. There was a downward trend in the standardized mortality rate of injury in children (AAPC=-5.54%, P<0.001). The standardized mortality rates of drowning and road traffic injury declined in both urban area and rural area (P<0.001). The mortality rate of accidental poisoning decreased in rural area (AAPC=-8.09%, P<0.001), but showed no significant change trend in urban area (P>0.05). The standardized mortality rate of suicide showed no significant change trend in urban area, but there was an increasing trend in the standardized mortality rate of suicide in rural children aged 10-14 years (AAPC=4.58%). No significant change trend was observed in mortality rate of falls in urban and rural children (P>0.05). The injury mortality rate showed obvious seasonality in children in Tianjin. Overall injury death risk and risk for drowning-caused death were highest in summer in both urban area and rural area. The risk for road traffic injury-related death was highest in autumn in urban area and in summer in rural area. The risk for death caused by accidental poisoning was highest in winter in both urban area and rural area. Conclusions: In recent decades, the injury mortality rate in children aged 0-14 years in Tianjin showed a decreasing trend. There is still a significant difference in the injury mortality level between urban area and rural area, to which close attention needs to be paid in the future policy development.

Comparisons of different extraction methods and solvents for saliva samples

INTRODUCTION

Changes in the categories and concentrations of salivary metabolites may be closely related to oral, intestinal or systemic diseases. To study salivary metabolites, the first analytical step is to extract them from saliva samples as much as possible, while reducing interferences to a minimum. Frequently used extraction methods are protein precipitation (PPT), liquid-liquid extraction (LLE) and solid-phase extraction (SPE), with various organic solvents. The types and quantities of metabolites extracted with different methods may vary greatly, but few studies have systematically evaluated them.

OBJECTIVES

This study aimed to select the most suitable methods and solvents for the extraction of saliva according to different analytical targets.

METHODS

An untargeted metabolomics approach based on liquid chromatography-mass spectrometry was applied to obtain the raw data. The numbers of metabolites, repeatability of the data and intensities of mass spectrometry signals were used as evaluation criteria.

RESULTS

PPT resulted in the highest coverage. Among the PPT solvents, acetonitrile displayed the best repeatability and the highest coverage, while acetone resulted in the best signal intensities for the extracted compounds. LLE with the mixture of chloroform and methanol was the most suitable for the extraction of small hydrophobic compounds.

CONCLUSION

PPT with acetonitrile or acetone was recommended for untargeted analysis, while LLE with the mixture of chloroform and methanol was recommended for small hydrophobic compounds.

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.

[The association between portal vein thrombosis and rebleeding after non-urgent endoscopic treatment of esophagogastric varices]

Objective: To investigate the association between portal vein thrombosis and rebleeding after non-urgent endoscopic treatment of esophagogastric varices. Methods: The cirrhotic patients with esophagogastric varices diagnosed in the People's Hospital of Zhengzhou University from January 2017 to March 2023 were retrospectively collected. The patients were divided into thrombotic group and non-thrombotic group according to the presence or absence of portal vein thrombosis. The failure rate of endoscopic treatment and rebleeding rate in different periods were compared between the two groups. Receiver operating characteristic (ROC) curve was used to select the best cutoff value of gastric varicose diameter that affected total rebleeding during follow-up in both groups. The influencing factors of rebleeding within 12 and 36 months in both groups were analyzed, and the influencing factors of rebleeding within 36 months in thrombus group were further analyzed. Results: A total of 106 patients were enrolled, including 53 patients in the thrombotic group [male 37, female 16, aged 18-78 (54±13) years] and 53 patients in the non-thrombotic group [male 37, female 16, aged 27-83 (55±12) years]. The follow-up time of the two groups were (20±15) and (25±15) months, respectively. The total rebleeding rate in the thrombotic group was higher than that in the non-thrombotic group [30.2% (16/53) vs 13.2% (7/53), P˂0.05]. The rebleeding rates within 6, 12, 24 and 36 months in the thrombotic group were higher than those in the non-thrombotic group [18.9% (10/53) vs 5.7% (3/53), 18.9% (10/53) vs 5.7% (3/53), 28.3% (15/53) vs 9.4% (5/53), 30.2% (16/53) vs 11.3% (6/53), all P˂0.05]. The best cut-off value of the diameter of gastric varices that affects the total rebleeding in the two groups was 10.4 mm (10 mm was selected as the best cut-off value for the convenience of practical clinical application). Hemoglobin ˂ 85 g/L (HR=0.202, 95%CI: 0.043-0.953, P=0.043), 10 mm ˂ the diameter of GV ≤ 15 mm (HR=5.321, 95%CI: 1.161-24.390, P=0.031) and endoscopic variceal ligation combined with endoscopic tissue adhesive injection (EVL+ETAI) (HR=7.172, 95%CI: 1.910-26.930, P=0.004) were the risk factors for the first gastroesophageal variceal rebleeding within 12 months after non-urgent endoscopic treatment. EVL+ETAI (HR=3.811, 95%CI: 1.441-10.084, P=0.007) and portal vein thrombosis (HR=4.026, 95%CI: 1.483-10.932, P=0.006) were the risk factors for the first gastroesophageal variceal rebleeding within 36 months after non-urgent endoscopic treatment. The study found that, 10 mm ˂ the diameter of GV ≤ 15 mm (HR=7.503, 95%CI: 1.568-35.890, P=0.012) was the risk factor for rebleeding within 36 months in the thrombotic group. Conclusion: Portal vein thrombosis is a risk factor for rebleeding after non-urgent endoscopic treatment of esophagogastric varices.

Gbdmr: identifying differentially methylated CpG regions in the human genome via generalized beta regressions

BACKGROUND

DNA methylation is a biochemical process in which a methyl group is added to the cytosine-phosphate-guanine (CpG) site on DNA molecules without altering the DNA sequence. Multiple CpG sites in a certain genome region can be differentially methylated across phenotypes. Identifying these differentially methylated CpG regions (DMRs) associated with the phenotypes contributes to disease prediction and precision medicine development.

RESULTS

We propose a novel DMR detection algorithm, gbdmr. In contrast to existing methods under a linear regression framework, gbdmr assumes that DNA methylation levels follow a generalized beta distribution. We compare gbdmr to alternative approaches via simulations and real data analyses, including dmrff, a new DMR detection approach that shows promising performance among competitors, and the traditional EWAS that focuses on single CpG sites. Our simulations demonstrate that gbdmr is superior to the other two when the correlation between neighboring CpG sites is strong, while dmrff shows a higher power when the correlation is weak. We provide an explanation of these phenomena from a theoretical perspective. We further applied the three methods to multiple real DNA methylation datasets. One is from a birth cohort study undertaken on the Isle of Wight, United Kingdom, and the other two are from the Gene Expression Omnibus database repository. Overall, gbdmr identifies more DMR CpGs linked to phenotypes than dmrff, and the simulated results support the findings.

CONCLUSIONS

Gbdmr is an innovative method for detecting DMRs based on generalized beta regression. It demonstrated notable advantages over dmrff and traditional EWAS, particularly when adjacent CpGs exhibited moderate to strong correlations. Our real data analyses and simulated findings highlight the reliability of gbdmr as a robust DMR detection tool. The gbdmr approach is accessible and implemented by R on GitHub: https://github.com/chengzhouwu/gbdmr .

Green and Low-Cost Alkali-Polyphenol Synergetic Self-Catalysis System Access to Fast Gelation of Self-Healable and Self-Adhesive Conductive Hydrogels for Self-Powered Triboelectric Nanogenerators

Biomass-based hydrogels have attracted great attention in flexible and sustainable self-powered power sources but struggled to fabricate in a green, high-efficiency, and low-cost manner. Herein, a novel and facile alkali-polyphenol synergetic self-catalysis system is originally employed for the fast gelation of self-healable and self-adhesive lignin-based conductive hydrogels, which can be regarded as hydrogel electrodes of flexible triboelectric nanogenerators (TENGs). This synergy self-catalytic system comprises aqueous alkali and polyphenol-containing lignin, in which alkali-activated ammonium persulfate (APS) significantly accelerates the generation of radicals and initiates the polymerization of monomers, while polyphenol acts as a stabilizer to avoid bursting polymerization from inherent radical scavenging ability. Furthermore, multiple hydrogen bonds between lignin biopolymers and polyacrylamide (PAM) chains impart lignin-based hydrogels with exceptional adhesiveness and self-healing properties. Intriguingly, the alkaline conditions not only contribute to the solubility of lignin but also impart superior ionic conductivity of lignin-based hydrogel that is applicable to flexible TENG in self-powered energy-saving stair light strips, which holds great promise for industrial applications of soft electronics.

Transcranial ultrasound estimation of viscoelasticity and fluidity in brain tumors aided by transcranial shear waves

Cerebral diseases, such as brain tumors, are intricately linked to the mechanical properties of brain tissues. Estimating the mechanical properties of brain tumors using transcranial ultrasound is a promising approach. However, the complexity of cranial features introduces challenges, such as ultrasound attenuation and interference from multidirectional transcranial shear waves induced by impact vibrations. To address these issues, this study proposes a transcranial ultrasound estimation method assisted by transcranial shear vibrations. Transcranial vibrations apply shear forces on the parietal bone, inducing unidirectional transcranial shear waves within brain tissue, as validated through simulations. Shear waves at different frequencies were captured via transcranial ultrasound, which were used to assess the viscoelasticity and fluidity of brain tumors. Transcranial experimental validations were conducted in 3D-printed models with tumor phantoms and ex vivo animal tumors. Vibration safety assessments were also performed. The results demonstrate that transcranial ultrasound can detect micron displacements induced by transcranial shear waves. In phantom and ex vivo animal experiments, speed distribution maps were employed to determine the size and location of one or two tumors enclosed in the skull model. The results revealed that the proposed approach could detect tumors with a minimum diameter of 0.8 cm and an inter-tumor distance of 0.8 cm. Notably, significant differences in viscoelasticity and fluidity between normal brain tissue and brain tumors were found (p<0.001). The maximum assessment errors for the elasticity, viscosity, and fluidity using transcranial ultrasound were 11.90%, 4.82%, and 0.73%, respectively, indicating that fluidity was more robust than viscoelasticity. The maximum accelerations of the skull were only 3.21 ms-2.

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

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