Distribution of antibiotic resistance genes and their pathogen hosts in duck farm environments in south-east coastal China

Livestock farms are major reservoirs of antibiotic resistance genes (ARGs) that are discharged into the environment. However, the abundance, diversity, and transmission of ARGs in duck farms and its impact on surrounding environments remain to be further explored. Therefore, the characteristics of ARGs and their bacterial hosts from duck farms and surrounding environment were investigated by using metagenomic sequencing. Eighteen ARG types which consist of 823 subtypes were identified and the majority conferred resistance to multidrug, tetracyclines, aminoglycosides, chloramphenicols, MLS, and sulfonamides. The floR gene was the most abundant subtype, followed by sul1, tetM, sul2, and tetL. ARG abundance in fecal sample was significantly higher than soil and water sample. Our results also lead to a hypothesis that Shandong province have been the most contaminated by ARGs from duck farm compared with other four provinces. PcoA results showed that the composition of ARG subtypes in water and soil samples was similar, but there were significant differences between water and feces samples. However, the composition of ARG subtypes were similar between samples from five provinces. Bacterial hosts of ARG subtypes were taxonomically assigned to eight phyla that were dominated by the Proteobacteria, Firmicutes, Bacteroidetes, and Actinobacteria. In addition, some human bacterial pathogens could be enriched in duck feces, including Enterococcus faecium, Acinetobacter baumannii, and Staphylococcus aureus, and even serve as the carrier of ARGs. The combined results indicate that a comprehensive overview of the diversity and abundance of ARGs, and strong association between ARGs and bacterial community shift proposed, and benefit effective measures to improve safety of antibiotics use in livestock and poultry farming. KEY POINTS: • ARG distribution was widespread in the duck farms and surroundings environment • ARG abundance on the duck farms was significantly higher than in soil and water • Human bacterial pathogens may serve as the vectors for ARGs.

A novel olfactory biosensor based on ZIF-8@SWCNT integrated with nanosome-AuNPs/Prussian blue for sensitive detection of hexanal

Hexanal is considered as an important volatile compound indicator for the assessment of freshness and maturity of foods. Therefore, sensitive and stable monitoring of hexanal is highly desired. Herein, an efficient receptor immobilization strategy based on ZIF-8@ Single-walled carbon nanotube (SWCNT) and nanosomes-AuNPs/Prussian blue (PB) was proposed for the development of olfactory biosensors. ZIF-8@SWCNT as dual support materials provided a high density of active sites for nanosomes loading. Moreover, the co-electrodeposition of nanosomes-AuNPs and PB on the sensor interface effectively amplified the electrochemical signal and maintained the activity of the receptor. The combination of ZIF-8@SWCNT with AuNPs/PB imparts excellent sensing performance of the biosensor with a wide detection range of 10-16-10-9 M, a low detection limit of 10-16 M for hexanal, and a long storage stability of 15 days. These results indicate that our biosensor can be a powerful tool for versatile applications in food and other related industries.

Fluorescent DNA-Silver nanoclusters in food safety detection: From synthesis to application

In recent years, the conventional preparation of silver nanoclusters (AgNCs) has attracted much attention due to their ultra-small size, tunable fluorescence, easy-to-engineer, as well as biocompatible material. Moreover, its great affinity towards cytosine bases on single-stranded DNA has led to the construction of biosensors, especially aptamers, for a broad variety of applications in food safety and environmental protection. In past years, numerous researchers paid attention to the construction of AgNCs aptasensor. Therefore, this review will be an effort to summarize the synthetic strategy along with the influences of factors on synthesis, categorize the sensing mechanism of aptamer-functionalized AgNCs biosensors, as well as their specific applications in food safety detection including heavy metal, toxin, and foodborne pathogenic bacteria. Furthermore, a brief conclusion and outlook regarding the prospects and challenges of their applications in food safety were drawn in line with the developments in DNA-AgNCs.

Impact of climate zones and seasons on indoor airborne microbial communities: Insights from a comprehensive analysis

Bacteria and fungi are ubiquitous throughout built environments and are suspended in the air, potentially affecting human health. However, the impacts of climate zones on the diversity, structure, and stochastic assembly of indoor airborne microbes remain unknown. This study comprehensively analyzed indoor airborne microbes across five climate zones in China during the summer and winter using high-throughput sequencing. The diversity and structure of indoor airborne communities vary across climatic zones. A random forest model was used to identify biomarkers in different climate zones. The results showed no relationship between the biomarkers and their rankings in mean relative abundance. The Sloan neutral model fitting results indicated that the impact of climate zones on the stochastic process in the assembly of indoor airborne microbes was considerably more important than that of seasons. Additionally, the influence of seasons on the diversity, structure, and stochastic assembly process of indoor airborne microbes differed among different climate zones. The diversity, structure, and stochastic assembly processes of bacteria present distinctive outcomes in climate zones and seasons compared with those of fungi. Overall, these findings indicate that customized strategies are necessary to manage indoor airborne microbial communities in each climate zone, season, and for specific microbial species.

Covalent modification of γ-cyclodextrin with geraniol: An antibacterial agent with good thermal stability, solubility and biocompatibility

Geraniol (Ger) is an essential oil molecule with excellent biological activity. High hydrophobicity and volatility limit its practical application. Cyclodextrins (CDs) are water-soluble cyclic oligosaccharides with hydrophobic cavities. Physical encapsulation of CDs to improve the solubility and stability of essential oil molecules is not satisfactory. Therefore, this study synthesized the γ-CD derivative (γ-CD-Ger) by grafting Ger onto γ-CD using a bromide-mediated method. Compared to the inclusion complexes (γ-CD/Ger) formed by both, the derivatives exhibit better solubility and thermal stability. The derivative has better antibacterial activity when the ratio of γ-CD to Ger was 1:2. In addition, the derivatives did not exhibit cytotoxic and hemolytic properties. These results indicate that this research provides a water-soluble antibacterial agent with a wide range of promising applications and offers new ideas for the application of alcohol hydrophobic molecules in aqueous systems.

A multihole nozzle controls recrystallization of high-moisture extruded maize starches: Effect of cooling die temperature

Hot extrusion is utilized for starch modification due to its high mechanical input and product output. Amylose recrystallization commences and primarily depends on intermolecular interactions after conventional extrusion. Hence, the design of a new component based on the existed extrusion system was aimed at facilitating molecular aggregation, potentially accelerating starch recrystallization. In this study, a nozzle sheet comprising 89 holes was integrated into the cooling die. The impact of the multihole nozzle on the structure and in vitro digestibility of extruded maize starches after retrogradation was examined at varying cooling die temperatures. The results showed that the nozzle-assembled extrusion system operated effectively without additional mechanical or yield losses. At 50 °C, the crystallinity of nozzle-produced starch was approximately 70 % higher than that of conventionally extruded starch, predominantly owing to the B-type allomorph of the amylose double helix. Recrystallized amylopectin was also found in these nozzle-produced starches, indicating that multihole nozzle-induced uniaxial elongational flow resulted in the rapid starch crystallization. The increased formation of recrystallized amylose led to improved molecular order in starch structures while reducing their digestibility. These findings revealed a new approach to improve starch crystallinity by incorporating a nozzle sheet in the extrusion process.

A fluorescent nanoprobe and paper-based nanofiber platform for detection and imaging of Fe3+ in actual samples and living cells

In this study, a novel fluorescent nanoprobe (ZIF-90@FSS) was constructed using a zeolite imidazolium ester skeleton (ZIF-90) incorporating sodium fluorescein within its porous structure. Notably, this nanoprobe exhibited regular fluorescence "off" detection performance of Fe3+ in actual samples and living cells. The concentration range of 0-150 ng/mL exhibited a lowest detection limit of 0.26 ng/mL. A nanofiber paper-based platform (VL78/ZIF-90@FSS) was further developed by coupling the prepared nanoprobe to a multi-dimensional fiber paper via CN bonds, enabling rapid visual white light colorimetric and fluorescence imaging of Fe3+ within 2 min. The constructed nanoprobe and its paper-based detection platforms demonstrated a stable recovery range in tap water, beer, and soy sauce samples during spiking-recovery assessments. The recovery rates ranged from 98.46 % to 108.24 % for the nanoprobe and from 91.75 % to 108.71 % for the nanofiber paper-based platform. Therefore, the developed nano-fluorescent sensor and paper-based nanofiber sensing platform offer a promising strategy for the visual detection of Fe3+, while also presenting novel and valuable methods to investigate the regulatory mechanisms of Fe3+ in living cells.

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

AIM

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

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

AIM

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

AIM

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

Leech extract alleviates idiopathic pulmonary fibrosis by TGF-β1/Smad3 signaling pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Leech, as a traditional Chinese medicine for the treatment of blood circulation and blood stasis, was also widely used to cure pulmonary fibrosis in China. In clinical practice, some traditional Chinese medicine preparation such as Shui Zhi Xuan Bi Hua Xian Tang and Shui Zhi Tong Luo Capsule composed of leech, could improve the clinical symptoms and pulmonary function in patients with idiopathic pulmonary fibrosis (IPF). However, the material basis of the leech in the treatment of IPF were not yet clear.

AIM OF THE STUDY

Screen out the components of leech that have the anti-pulmonary fibrosis effects, and further explore the therapeutic mechanism of the active components.

MATERIALS AND METHODS

In this study, the different molecular weight components of leech extract samples were prepared using the semi-permeable membranes with different pore sizes. The therapeutic effects of the leech extract groups with molecular weight greater than 10 KDa (>10 KDa group), between 3 KDa and 10 KDa (3-10 KDa group), and less than 3 KDa (<3 KDa group) on pulmonary fibrosis were firstly investigated by cell proliferation and cytotoxicity assay (MTT), cell wound healing assay, immunofluorescence staining (IF) and Western blot (WB) assay through the TGF-β1-induced fibroblast cell model. Then bleomycin-induced pulmonary fibrosis (BML-induced PF) mouse model was constructed to investigate the pharmacological activities of the active component group of leech extract in vivo. Pathological changes of the mouse lung were observed by hematoxylin-eosin staining (H&E) and Masson's trichrome staining (Masson). The hydroxyproline (HYP) content of lung tissues was quantified by HYP detection kit. The levels of extracellular matrix-related fibronectin (FN) and collagen type Ⅰ (Collagen Ⅰ), pyruvate kinase M2 (PKM2) monomer and Smad7 protein were determined via WB method. PKM2 and Smad7 protein were further characterized by IF assays.

RESULTS

Using TGF-β1-induced HFL1 cell line as a PF cell model, the in vitro results demonstrated that the >10 KDa group could significantly inhibited the cell proliferation and migration, downregulated the expression level of cytoskeletal protein vimentin and α-smooth muscle actin (α-SMA), and reduced the deposition of FN and Collagen Ⅰ. In the BML-induced PF mouse model, the >10 KDa group significantly reduced the content of HYP, downregulated the expression levels of FN and Collagen Ⅰ in lung tissues, and delayed the pathological changes of lung tissue structure. The results of WB and IF assays further indicated that the >10 KDa group could up-regulate the expression level of PKM2 monomer and Smad7 protein in the cellular level, thereby delaying the progression of pulmonary fibrosis.

CONCLUSIONS

Our study revealed that the >10 KDa group was the main material basis of the leech extract that inhibited pulmonary fibrosis through TGF-β1/Smad3 signaling pathway.

Differences of Typical Wuyi Rock Tea in Taste and Nonvolatiles Profile Revealed by Multisensory Analysis and LC-MS-Based Metabolomics

Wuyi Rock tea, specifically Shuixian and Rougui, exhibits distinct sensory characteristics. In this study, we investigated the sensory and metabolite differences between Shuixian and Rougui. Quantitative description analysis revealed that Rougui exhibited higher intensity in bitter, thick, harsh, and numb tastes, while Shuixian had stronger salty and umami tastes. Nontargeted metabolomics identified 151 compounds with 66 compounds identified as key differential metabolites responsible for metabolic discrimination. Most of the catechins and flavonoids were enriched in Rougui tea, while epigallocatechin-3,3'-di-O-gallate, epigallocatechin-3,5-di-O-gallate, gallocatechin-3,5-di-O-gallate, isovitexin, and theaflavanoside I were enriched in Shuixian tea. Catechins, kaempferol, quercetin, and myricetin derivatives were positively correlated with bitter taste and numb sensation. Sour taste was positively correlated to organic acids. Amino acids potentially contributed to salty and umami tastes. These results provide further insights into the taste characteristics and the relationship between taste attributes and specific metabolites in Wuyi Rock tea.

New Insights into the Umami and Sweet Taste of Oolong Tea: Formation of Enhancer N-(1-carboxyethyl)-6-(hydroxymethyl) pyridinium-3-ol (Alapyridaine) in Roasting Via Maillard Reaction

Roasting is pivotal for enhancing the flavor of Wuyi rock tea (WRT). A study investigated a novel compound that enhances the umami taste of WRT. Metabolomics of Shuixian tea (SXT) and Rougui tea (RGT) under light roasting (LR), medium roasting (MR), and heavy roasting (HR) revealed significant differences in nonvolatiles compounds. Compared LR reducing sugars and amino acids notably decreased in MR and HR, with l-alanine declining by 69%. Taste-guided fractionation identified fraction II-B as having high umami and sweet intensities. A surprising taste enhancer, N-(1-carboxyethyl)-6-(hydroxymethyl) pyridinium-3-ol (alapyridaine), was discovered and identified. It formed via the Maillard reaction, positively correlated with roasting in SXT and RGT. Alapyridaine levels were highest in SXT among the five oolong teas. Roasting tea with glucose increased alapyridaine levels, while EGCG inhibited its formation. HR-WRT exhibited enhanced umami and sweet taste, highlighting alapyridaine's impact on WRT's flavor profile. The formation of alapyridaine during the roasting process provides new insights into the umami and sweet perception of oolong tea.

Tongue-Coating Microbial and Metabolic Characteristics in Halitosis

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

Novel Umami Peptides from Mushroom (Agaricus bisporus) and Their Umami Enhancing Effect via Virtual Screening and Molecular Simulation

This study aimed to identify novel umami peptides in Agaricus bisporus and investigate their umami enhancing effect. We virtually screened 155 potential umami peptides from the ultrasound-assisted A. bisporus hydrolysate according to Q values, iUmami-SCM, Umami_YYDS, and Tastepeptides_DM models, and molecular docking. Five peptides (AGKNTNGSQF, DEAVARGATF, REESDFQSSF, SEETTTGVHH, and WNNDAFQSSTN) were synthesized for sensory evaluation and kinetic analysis. The result showed that the umami thresholds of the five peptides were in the range of 0.21-0.40 mmol/L. Notably, REESDFQSSF, SEETTTGVHH, and WNNDAFQSSTN had low dissociation constant (KD) values and high affinity for the T1R1-VFT receptor. The enhancing effect of the three peptides with MSG or IMP was investigated by sensory evaluation, kinetic analysis, and molecular dynamics simulations. In stable complexes, ARG_277 in T1R1 played a major role in umami peptide binding to T1R1-VFT. These results provide a theoretical basis for future screening of umami peptides and improving the umami taste of food containing mushrooms.

Tissue-Penetrating Ultrasound-Triggered Hydrogel for Promoting Microvascular Network Reconstruction

The microvascular network plays an important role in providing nutrients to the injured tissue and exchanging various metabolites. However, how to achieve efficient penetration of the injured tissue is an important bottleneck restricting the reconstruction of microvascular network. Herein, the hydrogel precursor solution can efficiently penetrate the damaged tissue area, and ultrasound triggers the release of thrombin from liposomes in the solution to hydrolyze fibrinogen, forming a fibrin solid hydrogel network in situ with calcium ions and transglutaminase as catalysts, effectively solving the penetration impedance bottleneck of damaged tissues and ultimately significantly promoting the formation of microvascular networks within tissues. First, the fibrinogen complex solution is effectively permeated into the injured tissue. Second, ultrasound triggered the release of calcium ions and thrombin, activates transglutaminase, and hydrolyzes fibrinogen. Third, fibrin monomers are catalyzed to form fibrin hydrogels in situ in the damaged tissue area. In vitro studies have shown that the fibrinogen complex solution effectively penetrated the artificial bone tissue within 15 s after ultrasonic triggering, and formed a hydrogel after continuous triggering for 30 s. Overall, this innovative strategy effectively solved the problem of penetration resistance of ultrasound-triggered hydrogels in the injured tissues, and finally activates in situ microvascular networks regeneration.

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

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

Keratin Formed Bioadhesive Ophthalmic Gel for the Bacterial Conjunctivitis Treatment

Keratin has the potential to function as the gel matrix in an ophthalmic formulation for the encapsulation of the macrolide antibiotic azithromycin. The quality of this formulation was thoroughly evaluated through various analyses, such as in vitro release assessment, rheological examination, intraocular retention studies in rabbits, assessment of bacteriostatic efficacy, and safety evaluations. It is worth mentioning that the gel demonstrated shear thinning properties and exhibited characteristics of an elastic solid, thereby confirming its structural stability. The gel demonstrated a notable affinity for mucosal surfaces in comparison to traditional azithromycin aqueous solutions. In vitro release testing revealed that drug release transpired via diffusion mechanisms, following a first-order kinetic release pattern. Additionally, the formulated gel exhibited remarkable antibacterial efficacy against Staphylococcus aureus and Pseudomonas aeruginosa in bacteriostatic evaluations. Lastly, safety assessments confirmed that the gel eye drops induced minimal irritation and displayed no apparent cytotoxicity, indicating their good safety and biocompatibility for ocular application. Thus, these findings indicated that the prepared azithromycin gel eye drops complied with the requisite standards for ophthalmic preparations.

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

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

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

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

Dynamics of magnetization at infinite temperature in a Heisenberg spin chain

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

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

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

Bioinspired Flexible Capacitive Sensor for Robot Positioning in Unstructured Environments

The evolution of bionic machines into intelligent robots to adapt to real scenarios is inseparable from positioning sensors. However, traditional positioning methods such as camera arrays, ultrasound, or GPS are limited in narrow concealed spaces, harsh temperatures, or dynamic light fields, which hinder the practical application of special robots. Here, we report a flexible sensor inspired by Gnathonemus petersii that enables robots to achieve contactless and high-precision spatial localization independent of the unstructured features of the environment. Sensors are obtained from low-cost materials (carbon nanotubes and polyimides) and simple structures (fibers) and preparation processes (spin-coating). Experiments and simulations confirmed the high resolution (<1 mm) of the sensor over a large distance detection range (>150 mm) and high bandwidth (0-520 MPa) of contact force. Moreover, the sensing capability is still feasible when the sensor is bent to various curvatures and not affected under harsh conditions such as ultralow temperatures (below -78 °C), ultrahigh temperatures (over 250 °C), darkness, or brightness. We demonstrate the practical potential of the proposed sensors for a biomimetic hyper-redundant continuum robot to locate and avoid collisions in unstructured environments.

Protein Deceleration and Sequencing Using Si3N4-CNT Hybrid Nanopores

Protein sequencing is crucial for understanding the complex mechanisms driving biological functions and is of utmost importance in molecular diagnostics and medication development. Nanopores have become an effective tool for single molecule sensing, however, the weak charge and non-uniform charge distribution of protein make capturing and sensing very challenging, which poses a significant obstacle to the development of nanopore-based protein sequencing. In this study, to facilitate capturing of the unfolded protein, highly charged peptide was employed in our simulations, we found that the velocity of unfolded peptide translocating through a hybrid nanopore composed of silicon nitride membrane and carbon nanotube is much slower compared to bare silicon nitride nanopore, it is due to the significant interaction between amino acids and the surface of carbon nanotube. Moreover, by introducing variations in the charge states at the boundaries of carbon nanotube nanopores, the competition and combination of the electrophoretic and electroosmotic flows through the nanopores could be controlled, we then successfully regulated the translocation velocity of unfolded proteins through the hybrid nanopores. The proposed hybrid nanopore effectively retards the translocation velocity of protein through it, facilitates the acquisition of ample information for accurate amino acid identification.

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

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

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

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

Predicting Protein Functions Based on Heterogeneous Graph Attention Technique

In bioinformatics, protein function prediction stands as a fundamental area of research and plays a crucial role in addressing various biological challenges, such as the identification of potential targets for drug discovery and the elucidation of disease mechanisms. However, known functional annotation databases usually provide positive experimental annotations that proteins carry out a given function, and rarely record negative experimental annotations that proteins do not carry out a given function. Therefore, existing computational methods based on deep learning models focus on these positive annotations for prediction and ignore these scarce but informative negative annotations, leading to an underestimation of precision. To address this issue, we introduce a deep learning method that utilizes a heterogeneous graph attention technique. The method first constructs a heterogeneous graph that covers the protein-protein interaction network, ontology structure, and positive and negative annotation information. Then, it learns embedding representations of proteins and ontology terms by using the heterogeneous graph attention technique. Finally, it leverages these learned representations to reconstruct the positive protein-term associations and score unobserved functional annotations. It can enhance the predictive performance by incorporating these known limited negative annotations into the constructed heterogeneous graph. Experimental results on three species (i.e., Human, Mouse, and Arabidopsis) demonstrate that our method can achieve better performance in predicting new protein annotations than state-of-the-art methods.

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Risk factors for taxane-induced peripheral neuropathy in patients with breast cancer

PURPOSE

This study investigated the clinical risk factors for peripheral neuropathy induced by docetaxel and albumin-bound paclitaxel (AP) in patients with breast cancer.

METHODS

This prospective observational study recruited 268 patients between March 2019 and December 2020. Patient information was obtained through the query system for laboratory test results, patient consultations, and scale evaluations. Neuropathic symptoms were followed up throughout and until 3 months after taxane chemotherapy. Univariate and multivariate analyses were used to find the risk factors for overall and moderate-severe taxane-induced peripheral neuropathy (TIPN).

RESULTS

Cumulative dose (odds ratio [OR] = 3.533, 95% confidence interval [CI]: 1.797-6.944, p < 0.001), body mass index (BMI) (OR = 2.926, 95% CI: 1.621-5.281, p < 0.001), body surface area (BSA) (OR = 1.724, 95% CI: 1.011-2.941, p = 0.045), and hypocalcemia (OR = 4.899, 95% CI: 1.518-15.811, p = 0.008) all increased the risk of TIPN. Only cumulative dose (OR = 2.577, 95% CI: 1.161-5.719, p = 0.020) and BSA (OR = 2.040, 95% CI: 1.073-3.877, p = 0.030) were independent risk factors for moderate-severe TIPN.

CONCLUSION

Cumulative dose, BMI, BSA, and hypocalcemia are all risk factors for overall TIPN, whereas cumulative dose and BSA are risk factors for moderate-severe TIPN. Patients with breast cancer who have high BMI, large BSA, hypocalcemia, and large cumulative dose may be at risk of TIPN, and intervention measures must be actively carried out for them.

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

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

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

OBJECTIVE

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

STUDY DESIGN

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

METHODS

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

RESULTS

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

CONCLUSION

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

Impacts of the development of acute-on-chronic liver failure and bacterial infections on β-cell function and glucose homeostasis in patients with liver cirrhosis

BACKGROUND

The pathogenesis involved in glucose metabolism disorders (GMDs) in patients with liver cirrhosis remains unclear.

AIMS

We investigated the effects of acute-on-chronic liver failure (ACLF) development and bacterial infections (BIs) on pancreatic β-cell function and glucose homeostasis in individuals with liver cirrhosis.

METHODS

A retrospective analysis was conducted on 327 patients experiencing acute deterioration of liver cirrhosis. Oral glucose tolerance tests (OGTTs) and OGTT-based β-cell function indices were employed to assess β-cell function and glucose homeostasis. Univariate and multivariate logistic regression analyses were employed to identify GMD-associated risk factors.

RESULTS

Both the development of ACLF and BIs significantly increased the prevalence of GMDs. Both ACLF and BIs markedly elevated the homeostasis model of assessment 2-insulin resistance (HOMA2-IR). ACLF significantly impaired glucose-stimulated insulin secretion, as evidenced by reduced insulinogenic index (IGI). Patients with GMDs exhibited significantly lower IGI levels than those without GMDs. Independent risk factors associated with GMDs were prothrombin activity (odds ratio [OR]=0.981, 95% confidence interval [CI]: 0.960-0.995), HOMA2-IR (OR=1.749, 95% CI: 1.130-2.707), and IGI (OR=0.963, 95% CI: 0.947-0.978).

CONCLUSIONS

In liver cirrhosis, the onset of ACLF impairs glucose-stimulated insulin secretion from β-cells. Both liver impairment and BIs contribute to increased insulin resistance, ultimately disturbing glucose homeostasis.

Optimal timing for awake prone positioning in Covid-19 patients: Insights from an observational study from two centers

BACKGROUND

The widespread application and interest in awake prone positioning stems from its ease and availability and its ability to enhance patients' oxygenation. Nevertheless, due to the absence of consensus over the regimen of awake prone positioning, the efficacy of awake prone positioning remains uncertain.

OBJECTIVE

To explore the optimal regimen for awake prone positioning, including the timing of initiation, ideal daily duration, and strategies for improving patient comfort and encouraging adherence.

DESIGN

Retrospective observational study.

SETTING(S)

Two university-affiliated hospitals in Shanghai.

PARTICIPANTS

Between December 2022 and February 2023, a total of 475 patients with COVID-19-related pneumonia who received awake prone positioning were observed.

METHODS

The data were collected from the hospital's electronic medical record system. The differentiation efficiency of peripheral blood oxygen saturation [SpO2]:fractional oxygen concentration in inspired air [FiO2] ratio at first awake prone positioning for different outcomes was tested by the area under the receiver operating characteristic curve. The Cox proportional hazard regression model was used to analyze the relationship between time to occurrence of 28-day outcomes and collected variables. Kaplan-Meier curves were plotted with the percentage of 28-day outcomes according to the SpO2:FiO2 ratio at first awake prone positioning after controlling covariates through Cox regression.

RESULTS

The best efficiency in predicting patient outcomes was achieved when the cutoff SpO2:FiO2 ratio at first awake prone positioning was 200. Patients with a reduced SpO2:FiO2 ratio (≤200) experienced more adverse respiratory outcomes (RR = 5.42, 95%CI [3.35, 8.76], p < 0·001) and higher mortality (RR = 16.64, 95%CI [5.53, 50.13], p < 0.001). Patients with a SpO2:FiO2 ratio of ≥200 at first awake prone positioning, longer duration between first awake prone positioning and admission, more awake prone positioning days, and better awake prone positioning completion were significantly protected from 28-day adverse respiratory outcomes and mortality.

CONCLUSIONS

Initiating awake prone positioning with a SpO2:FiO2 ratio exceeding 200, increasing the number of awake prone positioning days, prolonging the time between first awake prone positioning and admission, and achieving better completion of awake prone positioning were found to be significantly associated with reduced adverse respiratory outcomes and mortality.

REGISTRATION

ClinicalTrials.gov; No.: NCT05795751; URL: www.

CLINICALTRIALS

gov.

A Bilayer Method for Measuring Toughness and Strength of Dental Ceramics

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

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

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

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

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

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Affiliation(s)

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

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

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

A lightweight and gradient-stable neural layer

To enhance resource efficiency and model deployability of neural networks, we propose a neural-layer architecture based on Householder weighting and absolute-value activating, called Householder-absolute neural layer or simply Han-layer. Compared to a fully connected layer with d-neurons and d outputs, a Han-layer reduces the number of parameters and the corresponding computational complexity from O(d2) to O(d). The Han-layer structure guarantees that the Jacobian of the layer function is always orthogonal, thus ensuring gradient stability (i.e., free of gradient vanishing or exploding issues) for any Han-layer sub-networks. Extensive numerical experiments show that one can strategically use Han-layers to replace fully connected (FC) layers, reducing the number of model parameters while maintaining or even improving the generalization performance. We will also showcase the capabilities of the Han-layer architecture on a few small stylized models, and discuss its current limitations.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

DISCUSSION

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

SIGNIFICANCE

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

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

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

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

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

Integrative Dissection of Lignin Composition in Tartary Buckwheat Seed Hulls for Enhanced Dehulling Efficiency

The rigid hull encasing Tartary buckwheat seeds necessitates a laborious dehulling process before flour milling, resulting in considerable nutrient loss. Investigation of lignin composition is pivotal in understanding the structural properties of tartary buckwheat seeds hulls, as lignin is key determinant of rigidity in plant cell walls, thus directly impacting the dehulling process. Here, the lignin composition of seed hulls from 274 Tartary buckwheat accessions is analyzed, unveiling a unique lignin chemotype primarily consisting of G lignin, a common feature in gymnosperms. Furthermore, the hardness of the seed hull showed a strong negative correlation with the S lignin content. Genome-wide detection of selective sweeps uncovered that genes governing the biosynthesis of S lignin, specifically two caffeic acid O-methyltransferases (COMTs) and one ferulate 5-hydroxylases, are selected during domestication. This likely contributed to the increased S lignin content and decreased hardness of seed hulls from more domesticated varieties. Genome-wide association studies identified robust associations between FtCOMT1 and the accumulation of S lignin in seed hull. Transgenic Arabidopsis comt1 plants expressing FtCOMT1 successfully reinstated S lignin content, confirming its conserved function across plant species. These findings provide valuable metabolic and genetic insights for the potential redesign of Tartary buckwheat seed hulls.