Detection of lung cancer through SERS analysis of serum

Early detection and postoperative assessment are crucial for improving overall survival among lung cancer patients. Here, we report a non-invasive technique that integrates Raman spectroscopy with machine learning for the detection of lung cancer. The study encompassed 88 postoperative lung cancer patients, 73 non-surgical lung cancer patients, and 68 healthy subjects. The primary aim was to explore variations in serum metabolism across these cohorts. Comparative analysis of average Raman spectra was conducted, while principal component analysis was employed for data visualization. Subsequently, the augmented dataset was used to train convolutional neural networks (CNN) and Resnet models, leading to the development of a diagnostic framework. The CNN model exhibited superior performance, as verified by the receiver operating characteristic curve. Notably, postoperative patients demonstrated an increased likelihood of recurrence, emphasizing the crucial need for continuous postoperative monitoring. In summary, the integration of Raman spectroscopy with CNN-based classification shows potential for early detection and postoperative assessment of lung cancer.

A universal ANN-to-SNN framework for achieving high accuracy and low latency deep Spiking Neural Networks

Spiking Neural Networks (SNNs) have become one of the most prominent next-generation computational models owing to their biological plausibility, low power consumption, and the potential for neuromorphic hardware implementation. Among the various methods for obtaining available SNNs, converting Artificial Neural Networks (ANNs) into SNNs is the most cost-effective approach. The early challenges in ANN-to-SNN conversion work revolved around the susceptibility of converted SNNs to conversion errors. Some recent endeavors have attempted to mitigate these conversion errors by altering the original ANNs. Despite their ability to enhance the accuracy of SNNs, these methods lack generality and cannot be directly applied to convert the majority of existing ANNs. In this paper, we present a framework named DNISNM for converting ANN to SNN, with the aim of addressing conversion errors arising from differences in the discreteness and asynchrony of network transmission between ANN and SNN. The DNISNM consists of two mechanisms, Data-based Neuronal Initialization (DNI) and Signed Neuron with Memory (SNM), designed to respectively address errors stemming from discreteness and asynchrony disparities. This framework requires no additional modifications to the original ANN and can result in SNNs with improved accuracy performance, simultaneously ensuring universality, high precision, and low inference latency. We verify it experimentally on challenging object recognition datasets, including CIFAR10, CIFAR100, and ImageNet-1k. Experimental results show that the SNN converted by our framework has very high accuracy even at extremely low latency.

Chiral carbon dots derived from tryptophan and threonine for enantioselective sensing of L/D-Lysine

Presently, most fluorescent probes for amino acid enantiomers detection require metal ions participation, which greatly increases the detection steps and costs, and affects the accuracy of detection results. To solve this problem, a dual pattern recognition sensor of chiral carbon dots (L-Try-Thr-CDs) with a quantum yield of 36.23 % was prepared by a one-step solvothermal method for the highly selective detection of lysine (Lys) enantiomers. Under optimal experimental conditions, the fluorescence and circular dichroism (CD) signals of the obtained L-Try-Thr-CDs could rapidly and effectively responded to L-Lys with limits of detection (LOD) of 16.51 nM and 24.38 nM, respectively, much lower than previously reported sensors. Importantly, the L-Try-Thr-CDs as a dual-mode sensor could not only detect amino acid enantiomers and simplify the steps, but also avoid inaccurate detection results due to unstable metal ions. Furthermore, the L-Try-Thr-CDs could detect L-Lys in living cells via a fluorescence microscope because of their excellent fluorescence characteristics and low toxicity. These results indicated that the dual-mode sensor not only provided a practical strategy for the design of new fluorescent probes, but also possessed outstanding application prospects in the accurate detection of lysine enantiomers.

Novel alternative tools for metastatic pheochromocytomas/paragangliomas prediction

OBJECTIVE

The existing prediction models for metastasis in pheochromocytomas/paragangliomas (PPGLs) showed high heterogeneity in different centers. Therefore, this study aimed to establish new prediction models integrating multiple variables based on different algorithms.

DESIGN AND METHODS

Data of patients with PPGLs undergoing surgical resection at the Peking Union Medical College Hospital from 2007 to 2022 were collected retrospectively. Patients were randomly divided into the training and testing sets in a ratio of 7:3. Subsequently, decision trees, random forest, and logistic models were constructed for metastasis prediction with the training set and Cox models for metastasis-free survival (MFS) prediction with the total population. Additionally, Ki-67 index and tumor size were transformed into categorical variables for adjusting models. The testing set was used to assess the discrimination and calibration of models and the optimal models were visualized as nomograms. Clinical characteristics and MFS were compared between patients with and without risk factors.

RESULTS

A total of 198 patients with 59 cases of metastasis were included and classified into the training set (n = 138) and testing set (n = 60). Among all models, the logistic regression model showed the best discrimination for metastasis prediction with an AUC of 0.891 (95% CI, 0.793-0.990), integrating SDHB germline mutations [OR: 96.72 (95% CI, 16.61-940.79)], S-100 (-) [OR: 11.22 (95% CI, 3.04-58.51)], ATRX (-) [OR: 8.42 (95% CI, 2.73-29.24)] and Ki-67 ≥ 3% [OR: 7.98 (95% CI, 2.27-32.24)] evaluated through immunohistochemistry (IHC), and tumor size ≥ 5 cm [OR: 4.59 (95% CI, 1.34-19.13)]. The multivariate Cox model including the above risk factors also showed a high C-index of 0.860 (95% CI, 0.810-0.911) in predicting MFS after surgery. Furthermore, patients with the above risk factors showed a significantly poorer MFS (P ≤ 0.001).

CONCLUSIONS

Models established in this study provided alternative and reliable tools for clinicians to predict PPGLs patients' metastasis and MFS. More importantly, this study revealed for the first time that IHC of ATRX could act as an independent predictor of metastasis in PPGLs.

Spatial-temporal trends in leprosy burden and its associations with socioeconomic and physical geographic factors: results from the Global Burden of Disease Study 2019

OBJECTIVES

The purpose of our study was to assess the multiscalar changes in leprosy burden and its associated risk factors over the last three decades.

STUDY DESIGN

We conducted an in-depth examination of leprosy's spatial-temporal trends at multiple geographical scale (global, regional, and national), utilizing information from Global Burden of Disease, Injuries, and Risk Factors Study (GBD 2019).

METHODS

Incidence and the estimated annual percentage change (EAPC) in age-standardized incidence rate (ASIR) of leprosy were determined, with countries categorized based on leprosy incidence changes. We examined socioeconomic and physical geography influences on leprosy incidence via Spearman correlation analysis, using ternary phase diagrams to reveal the synergetic effects on leprosy occurrence.

RESULTS

Globally, incident cases of leprosy decreased by 27.86% from 1990 to 2019, with a reduction in ASIR (EAPC = -2.53), yet trends were not homogeneous across regions. ASIR and EAPC correlated positively with sociodemographic index (SDI), and an ASIR growth appeared in high SDI region (EAPC = 3.07). Leprosy burden was chiefly distributed in Tropical Latin America, Oceania, Central Sub-Saharan Africa, and South Asia. Negative correlations were detected between the incidence of leprosy and factors of SDI, GDP per capita, urban population to total population, and precipitation, whereas the number of refugee population, temperature, and elevation showed opposite positive results.

CONCLUSIONS

Despite a global decline in leprosy over the past three decades, the disparities of disease occurrence at regional and national scales still persisted. Socioeconomic and physical geographic factors posed an obvious influence on the transmission risk of leprosy. The persistence and regional fluctuations of leprosy incidence necessitate the ongoing dynamic and multilayered control strategies worldwide in combating this ancient disease.

The spatial spillover effects of clean energy consumption and production on sustainable economic development in China

The massive consumption of fossil energy has resulted in high CO2 emissions, posing a formidable challenge to global sustainable economic development (SED). As countries endeavor to shift from fossil to clean energy sources to achieve SED, research on the impact of clean energy is scarce, and quantitative analysis is lacking. This study measured China's SED and used a spatial econometric model to examine the impact of clean energy consumption and production on SED across 30 provinces in China from 2008 to 2020. Results show that (1) China's SED exhibits significant positive spatial autocorrelation characteristics, forming a "point-to-area" development pattern. (2) Clean energy consumption, production, and consumption structure all contribute to the promotion of SED in the region and have positive spatial spillover effects. (3) A considerable regional disparity exists in the spatial impact of clean energy on SED. The eastern and central regions have significant positive spatial spillover effects, whereas the western region is opposite. Notably, the estimated coefficient of the spatial Durbin model is relatively small, reflecting China's ongoing transition to clean energy and its limited role in promoting economic sustainability. Joint efforts and differentiated policies are essential to develop clean energy and sustainable economic.

Analysis on status quo and related factors of delays in diagnosis and treatment of breast cancer in Ningxia Hui Autonomous Region

This study aimed to explore factors contributing to the delays in the diagnosis and treatment of breast cancer (BC) in Ningxia Hui Autonomous Region. We conducted a cohort analysis of 1012 patients with BC diagnosed at the General Hospital of Ningxia Medical University between January 2018 and December 2019. Sociodemographic data were collected through questionnaires, and clinical data were gathered and analyzed from relevant databases. Furthermore, observations were made regarding delays in the diagnosis and treatment of BC, followed by an analysis of the correlations between patient delay and both sociological factors within the population and clinical factors specific to patients with BC. Subsequently, the factors associated with patient delay and system delay were examined using Cox regression analysis, along with the inclusion of neoadjuvant therapy. In the prevention and treatment of BC in Ningxia, the patient delay rate was 33.20%, the diagnosis delay rate was 17.89%, the treatment delay rate was 0.0099% and the system delay rate was 41.60%. There was a higher proportion of patient delay and system delay in aged patients (age ≥ 61 years) with rural registered permanent residence (RPR), multiple clinical symptoms (such as nipple spillage, axillary abnormalities, etc), a T4 tumor size classification, and the initial use of neoadjuvant therapy. Besides, significant positive correlations were observed between patient delay and system delay time with BC stage. Patients aged 51 to 60 and those with molecular types (Limanal1B: ki-67 > 14%, Limanal1B: HER-2 positive) were prone to patient delay, whereas molecular characteristics influenced system delay, unrelated to sociodemographic factors. The study identifies significant age, residency, and tumor molecular subtype correlations with diagnostic and treatment delays in Ningxia's patients with BC, predominantly affecting women aged 41 to 60, especially urban dwellers. These findings underscore the need for targeted interventions to reduce delays and improve BC care in this region.

Diurnal emission variation of ozone precursors: Impacts on ozone formation during Sep. 2019

With the issue of ozone (O3) pollution having increasingly gained visibility and prominence in China, the Chinese government explored various policies to mitigate O3 pollution. In some provinces and cities, diurnal regulations of O3 precursor were implemented, such as shifting O3 precursor emission processes to nighttime and offering preferential refueling at night. However, the effectiveness of these policies remains unverified, and their impact on the O3 generation process requires further elucidation. In this study, we utilized a regional climate and air quality model (WRF-Chem, v4.5) to test three scenarios aimed at exploring the impact of diurnal industry emission variation of O3 precursors on O3 formation. Significant O3 variations were observed mainly in urban areas. Shifting volatile organic compounds (VOCs) to nighttime have slight decreased daytime O3 levels while moving nitrogen oxides (NOx) to nighttime elevates O3 levels. Simultaneously moving both to nighttime showed combined effects. Process analysis indicates that the diurnal variation in O3 was mainly attributed to chemical process and vertical mixing in urban areas, while advection becomes more important in non-urban areas, contributing to the changes in O3 and O3 precursors levels through regional transportation. Further photochemical analysis reveals that the O3 photochemical production in urban areas was affected by reduced daytime O3 precursors emissions. Specifically, decreasing VOCs lowered the daytime O3 production by reducing the ROx radicals (ROx = HO + HO˙2 + RO˙2), whereas decreasing NOx promoted the daytime O3 production by weakening ROx radical loss. Our results demonstrate that diurnal regulation of O3 precursors will disrupt the ROx radical and O3 formation in local areas, resulting in a change in O3 concentration and atmospheric oxidation capacity, which should be considered in formulating new relevant policies.

scGREAT: Transformer-based deep-language model for gene regulatory network inference from single-cell transcriptomics

Gene regulatory networks (GRNs) involve complex and multi-layer regulatory interactions between regulators and their target genes. Precise knowledge of GRNs is important in understanding cellular processes and molecular functions. Recent breakthroughs in single-cell sequencing technology made it possible to infer GRNs at single-cell level. Existing methods, however, are limited by expensive computations, and sometimes simplistic assumptions. To overcome these obstacles, we propose scGREAT, a framework to infer GRN using gene embeddings and transformer from single-cell transcriptomics. scGREAT starts by constructing gene expression and gene biotext dictionaries from scRNA-seq data and gene text information. The representation of TF gene pairs is learned through optimizing embedding space by transformer-based engine. Results illustrated scGREAT outperformed other contemporary methods on benchmarks. Besides, gene representations from scGREAT provide valuable gene regulation insights, and external validation on spatial transcriptomics illuminated the mechanism behind scGREAT annotation. Moreover, scGREAT identified several TF target regulations corroborated in studies.

Construction of Functional Phenolic Resin and Carbon Hollow Spheres by Manipulating Structural Inhomogeneity

Hollow carbonaceous spheres are extraordinarily attractive for their unique structural features and wide applications in various fields. Herein, a facile and effective synthesis methodology based on the extended Stöber process for construction of phenolic resin hollow spheres has been presented. Combined with a series of characterization techniques, the synthesis process was systematically investigated, and a possible synthesis mechanism was proposed. It is revealed that the structural inhomogeneity of the polymer product achieved by using dodecylamine and alkane is responsible for the formation of hollow architecture, which depends on spontaneous selective dissolution during the synthesis process. Different metal-doped carbonaceous hollow spheres can be obtained by introducing corresponding precursors into the synthetic system and meeting requirements of different application fields. This work presented a novel synthesis strategy of hollow carbonaceous spheres, which is significant for building a new platform of advanced functional carbon-based composites.

Omics-based approaches for discovering active ingredients and regulating gut microbiota of Actinidia arguta exosome-like nanoparticles

Exosome-like nanoparticles (ELNs) are novel naturally occurring plant ultrastructures and contain unique bioactive components. However, the potential applications and biological functions of plant ELNs, especially in the context of health promotion and disease prevention, remain largely unexplored. This study aimed to explore the biological activities and functional mechanisms of Actinidia arguta-derived exosome-like nanoparticles (AAELNs). We reported the development of AAELNs, which possess particle sizes of 157.8 nm and a negative surface charge of -23.07 mV, uptaking by RAW264.7 cells, and reduction of oxidative stress by decreasing the activity of GSH-Px and T-SOD and increasing the content of MDA. Through the use of high-throughput sequencing technology, 12 known miRNA families and 23 additional miRNAs were identified in AAELNs, GO and KEGG term enrichment analysis revealed the potential of AAELNs-miRNAs in modulating neural-relevant behaviors. Additionally, LC-MS/MS analysis detected a total of 32 major lipid classes, 430 lipid subclasses, and 1345 proteins in AAELNs. Furthermore, in vivo fluorescence disappearance and in vitro fermentation experiments demonstrated that AAELNs were able to enter the colon and improve the microbial structure. These findings suggest that AAELNs could serve as nanoshuttles in food, potentially offering health-enhancing properties.

[Salivary carcinoma showing thymus-like differentiation: clinicopathological analysis of 7 cases]

Objective: To analyze the clinicopathological features of salivary carcinoma with thymus-like differentiation(CASTLE). Methods: Cases diagnosed with salivary CASTLE from January 2020 to December 2023 were collected and selected from the Department of Oral Pathology, Shanghai Ninth People's Hospital,Shanghai Jiao Tong University School of Medicine. A total of 7 cases of salivary CASTLE were identified. All the cases originated from parotid. There were 3 males and 4 females. The patients' age range was 11-70 years.The clinical, microscopic, immunohistochemical and prognostic features of these cases were analyzed. Results: The duration of disease ranged from 1 month to 1 year, and 1 patient had facial numbness and 1 with swelling sensation occasionally. Radiographically, 4 cases showed malignant signs. Microscopically, 4 cases involved in parotid gland, and all the tumors had different degrees of lymphoid tissue background. The tumor cells arranged in nests, 5 cases with lymphoepithelial carcinoma-like and 2 cases with squamous cell carcinoma morphology. The tumor cells expressed CD5 and CD117 proteins diffusely in lymphoepithelial carcinoma-like cases. However, the tumor cells expressed CD5 diffusely and CD117 focally in cases with squamous cell carcinoma morphology. All the cases had no Epstein-Barr virus infection. Among the 6 patients with follow-up information, all of them underwent postoperative radiotherapy, and none of them had local recurrence and lymph node metastasis. Conclusions: Salivary CASTLE is a rare tumor, it should be distinguished from lymphoepithelial carcinoma and squamous cell carcinoma. The patients often have better prognosis and CD5 protein expression has a valuable role in the differential diagnosis.

Quantum simulation of conical intersections

We explore the simulation of conical intersections (CIs) on quantum devices, setting the groundwork for potential applications in nonadiabatic quantum dynamics within molecular systems. The intersecting potential energy surfaces of H3+ are computed from a variance-based contracted quantum eigensolver. We show how the CIs can be correctly described on quantum devices using wavefunctions generated by the anti-Hermitian contracted Schrödinger equation ansatz, which is a unitary transformation of wavefunctions that preserves the topography of CIs. A hybrid quantum-classical procedure is used to locate the seam of CIs. Additionally, we discuss the quantum implementation of the adiabatic to diabatic transformation and its relation to the geometric phase effect. Results on noisy intermediate-scale quantum devices showcase the potential of quantum computers in dealing with problems in nonadiabatic chemistry.

Emergency Department Trauma Activation Fees by Payer Type

This cross-sectional study examines the wide variations in prices of emergency medical services at US hospitals.

DeepSeq2Drug: An expandable ensemble end-to-end anti-viral drug repurposing benchmark framework by multi-modal embeddings and transfer learning

Drug repurposing is promising in multiple scenarios, such as emerging viral outbreak controls and cost reductions of drug discovery. Traditional graph-based drug repurposing methods are limited to fast, large-scale virtual screens, as they constrain the counts for drugs and targets and fail to predict novel viruses or drugs. Moreover, though deep learning has been proposed for drug repurposing, only a few methods have been used, including a group of pre-trained deep learning models for embedding generation and transfer learning. Hence, we propose DeepSeq2Drug to tackle the shortcomings of previous methods. We leverage multi-modal embeddings and an ensemble strategy to complement the numbers of drugs and viruses and to guarantee the novel prediction. This framework (including the expanded version) involves four modal types: six NLP models, four CV models, four graph models, and two sequence models. In detail, we first make a pipeline and calculate the predictive performance of each pair of viral and drug embeddings. Then, we select the best embedding pairs and apply an ensemble strategy to conduct anti-viral drug repurposing. To validate the effect of the proposed ensemble model, a monkeypox virus (MPV) case study is conducted to reflect the potential predictive capability. This framework could be a benchmark method for further pre-trained deep learning optimization and anti-viral drug repurposing tasks. We also build software further to make the proposed model easier to reuse. The code and software are freely available at http://deepseq2drug.cs.cityu.edu.hk.

[Clinical value of the implication of extracorporeal carbon dioxide removal in patients with acute respiratory distress syndrome]

Extracorporeal carbon dioxide removal (ECCO2R) is a respiratory support technique based on extra-pulmonary gas exchange, which can effectively remove carbon dioxide generated in-vivo, reducing the requirements of respiratory support from mechanical ventilation. With improvements in extracorporeal life support technologies and increasing clinical experience, ECCO2R has potential value in clinical application with acute respiratory distress syndrome (ARDS). This review article discusses the principles of ECCO2R, its relevant indications for ARDS, clinical evidence, existing issues, and future directions, aiming to provide more references for the application in ARDS.

A Novel Induction-Type Pressure Sensor based on Magneto-Stress Impedance and Magnetoelastic Coupling Effect for Monitoring Hand Rehabilitation

Visualization of training effectiveness is critical to patients' confidence and eventual rehabilitation. Here, an innovative magnetoinductive pressure sensor is proposed for monitoring hand rehabilitation in stroke hemiplegic patients. It couples the giant magneto and stress-impedance effects of a square spiral amorphous wire with the giant magnetoelastic effect of a polymer magnet (NdFeB@PDMS). The addition of the magnetoelastic layer results in a sensitivity improvement of 178%, a wide sensing range (up to 1 MPa), fast response/recovery times (40 ms), and excellent mechanical robustness (over 15 000 cycles). Further integration with an LC oscillation circuit enables frequency adjustment into the MHz range resulting in a sensitivity of 6.6% kPa-1 and outstanding linearity (R2 =  0.99717) over a stress range of up to 100 kPa. When attached to a commercial split-fingerboard, the sensor is capable of dynamically monitoring the force in each finger, providing a reading of the rehabilitation process. Unlike conventional inductive sensors, the sensor is based on an inductive force-responsive material (amorphous wire), which significantly boosts the sensitivity. The approach also demonstrates the potential of magnetoelasticity in static pressure sensing, which is highly sensitive to dynamic pressure only through electromagnetic induction. This makes it more suitable for long-term and continuous human health monitoring.

Spatiotemporal Evolution of Developing Palate in Mice

The intricate formation of the palate involves a series of complex events, yet its mechanistic basis remains uncertain. To explore major cell populations in the palate and their roles during development, we constructed a spatiotemporal transcription landscape of palatal cells. Palate samples from C57BL/6 J mice at embryonic days 12.5 (E12.5), 14.5 (E14.5), and 16.5 (E16.5) underwent single-cell RNA sequencing (scRNA-seq) to identify distinct cell subsets. In addition, spatial enhanced resolution omics-sequencing (stereo-seq) was used to characterize the spatial distribution of these subsets. Integrating scRNA-seq and stereo-seq with CellTrek annotated mesenchymal and epithelial cellular components of the palate during development. Furthermore, cellular communication networks between these cell subpopulations were analyzed to discover intercellular signaling during palate development. From the analysis of the middle palate, both mesenchymal and epithelial populations were spatially segregated into 3 domains. The middle palate mesenchymal subpopulations were associated with tooth formation, ossification, and tissue remodeling, with initial state cell populations located proximal to the dental lamina. The nasal epithelium of the palatal shelf exhibited richer humoral immune responses than the oral side. Specific enrichment of Tgfβ3 and Pthlh signals in the midline epithelial seam at E14.5 suggested a role in epithelial-mesenchymal transition. In summary, this study provides high-resolution transcriptomic information, contributing to a deeper mechanistic understanding of palate biology and pathophysiology.

[Techniques for quantifying endotypes of obstructive sleep apnea]

Obstructive sleep apnea (OSA) is the frequent occurrence of apnea and/or hypopnea during sleep, leading to intermittent hypoxia, hypercapnia, and disruption of sleep architecture, further resulting in multisystem damage. The pathophysiological mechanisms include abnormal anatomical structure, low arousal threshold, high loop gain, and poor muscle reactivity, etc. As there are individual differences in the underlying mechanisms of OSA (i.e. endotypes), the effectiveness of treatment and prognosis may also vary according to these characteristics. Understanding the endotype of OSA is critical to understanding which patients are most likely to benefit from non-invasive ventilation therapy. Quantification of endotypes is central to the precision treatment of OSA and may provide the basis for accurate clinical treatment of OSA based on endotypes.

Early-life risk factors, accelerated biological aging and the late-life risk of mortality and morbidity

BACKGROUND

Early-life exposure increases health risks throughout an individual's lifetime. Biological aging is influenced by early-life risks as a key process of disease development, but whether early-life risks could accelerate biological aging and elevate late-life mortality and morbidity risks remains unknown. Knowledge is also limited on the potential moderating role of healthy lifestyle.

METHODS

We investigate associations of three early-life risks around birth, breastfeeding, maternal smoking and birth weight, with biological aging of 202 580 UK Biobank participants (54.9 ± 8.1 years old). Biological aging was quantified as KDM-BA, PhenoAge and frailty. Moderate alcohol intake, no current smoking, healthy diet, BMI <30 kg/m2 and regular physical activity were considered as healthy lifestyles. Mortality and morbidity data were retrieved from health records.

RESULTS

Individual early-life risk factors were robustly associated with accelerated biological aging. A one-unit increase in the 'early-life risk score' integrating the three factors was associated with 0.060 (SE=0.0019) and 0.036-unit (SE = 0.0027) increase in z-scored KDM-BA acceleration and PhenoAge acceleration, respectively, and with 22.3% higher odds (95% CI: 1.185-1.262) of frailty. Increased chronological age and healthy lifestyles could mitigate the accelerations of KDM-BA and PhenoAge, respectively. Associations of early-life risk score with late-life mortality and morbidity were mediated by biological aging (proportions: 5.66-43.12%). KDM-BA and PhenoAge accelerations could significantly mediate the impact on most outcomes except anxiety, and frailty could not mediate the impact on T2D.

CONCLUSION

Biological aging could capture and mediate the late-life health risks stemming from the early-life risks, and could be potentially targeted for healthy longevity promotion.

Hazel Leaf Polyphenol Extract Alleviated Cisplatin-Induced Acute Kidney Injury by Reducing Ferroptosis through Inhibiting Hippo Signaling

Derived from hazelnuts, hazel leaf has been utilized in traditional folk medicine for centuries in countries such as Portugal, Sweden, and Iran. In our previous investigations, we conducted a preliminary assessment of the hazel leaf polyphenol extract (referred to as ZP) and identified nine compounds, such as kaempferol and chlorogenic acid, in its composition. ZP has shown promising properties as an antioxidant and anti-inflammatory agent. Our research has revealed that ZP has protective effects against cisplatin-induced acute kidney injury (AKI). We conducted a comprehensive examination of both the pathological and ultrastructural aspects and found that ZP effectively ameliorated renal tissue lesions and mitigated mitochondrial damage. Moreover, ZP significantly suppressed malondialdehyde levels while increasing glutathione and catalase concentrations in the kidneys of AKI-induced mice. ZP decreased the number of apoptotic cells and decreased pro-apoptotic protein expression in the kidneys of mice and human renal tubular epithelial cells (HK-2). Furthermore, treatment with ZP increased the levels of proteins marking anti-ferroptosis, such as GPX4, FTH1, and FSP1, in experiments both in vivo and in vitro. We elucidated the underlying mechanisms of ZP's actions, revealing its inhibitory effect on Yap phosphorylation and its regulation of Lats expression, which exert a protective influence on the kidneys. Furthermore, we found that inhibiting the Hippo pathway compromised ZP's nephroprotective effects in both in vitro and in vivo studies. In summary, this research shows that ZP exhibits renoprotective properties, effectively reducing oxidative damage, apoptosis, and ferroptosis in the kidneys by targeting the Hippo pathway.

[Analysis of prevalence status and influencing factors of e-cigarette use among secondary school students in Heilongjiang Province]

Objective: To describe the current situation and influencing factors of e-cigarette use among secondary school students in Heilongjiang Province to provide evidence for formulating provincial youth e-cigarette prevention and control strategies. Methods: A multi-stage stratified cluster probability sampling method was adopted in 2021, with 8 340 students in 180 classes from 56 primary and high schools in 10 monitoring districts and counties in Heilongjiang Province. The students in the selected classes filled out a unified questionnaire by themselves. SAS 9.4 software was used for data cleansing, sample weighting, and analysis. Chi-squared tests were used to compare the differences between groups, and a two-level logistic regression model was used to analyze the influencing factors of e-cigarette use among secondary school students. Results: A total of 8 329 survey questionnaires were included in the analysis. The prevalence rates of ever and current e-cigarette use among secondary school students in Heilongjiang Province were 18.27% and 5.46%, respectively. In terms of ever e-cigarette use, the rate of boys (23.94%) was higher than that of girls (12.35%). The rate of vocational high school students (39.18%) was higher than that of general high school students (24.11%) and than that of junior school students (11.27%). In terms of current e-cigarette use, the rate of boys (7.08%) was higher than that of girls (3.76%). The rate of vocational high school students (14.56%) was higher than that of general high school students (7.70%) and than that of junior school students (2.67%). The rates of ever and current e-cigarette use were relatively higher in each subgroup, including "weekly allowance more than 40 Yuan" "one of the student's parents, friends or teachers was smoker" "smoked cigarettes now" and "saw e-cigarette advertisements". A two-level logistic regression model showed that the following factors were the influencing factors of current use of e-cigarettes among secondary school students, including gender, whether they were current cigarette smokers, the smoking status of their close friends, if they saw teachers smoked in the school, noticed e-cigarette advertisements, and e-cigarette addictive cognition. Conclusions: The prevalence rates of ever and current e-cigarette use among secondary school students in Heilongjiang Province were high. E-cigarette advertisements, the smoking status of their close friends, and whether they saw teachers smoking in the school were the main factors affecting e-cigarette use among secondary school students in Heilongjiang Province. It is necessary to focus on constructing smoke-free environments and increase health education related to e-cigarette knowledge on risk in developing a smoke-free campus in the whole province.

[Comparison of efficacy between short-term personalized vestibular rehabilitation supervised by special personnel and fixed vestibular rehabilitation on recurrent peripheral vertigo]

Objective: To explore the efficacy of short-term personalized vestibular rehabilitation supervised by special personnel (ST-PVR) versus fixed vestibular rehabilitation (FVR) on decompensated recurrent peripheral vertigo. Methods: A randomized controlled trial was carried out. Patients diagnosed with decompensated recurrent vertigo in the clinic of Eye & ENT Hospital, Fudan University from January to December 2018 were randomly allocated into FVR and ST-PVR groups via computer-generated randomization. The FVR group received fixed scheme involving gaze stabilization exercises, habituation exercises, balance and gait training, while the ST-PVR group received individualized training programs based on symptoms and vestibular function examination results, with adjustments made according to the progress of recovery. Patient symptoms and vestibular function improvement were assessed using the dizziness handicap inventory (DHI), activities-specific balance confidence (ABC), self-rating anxiety scale (SAS), caloric test, and sensory organization test (SOT) at 2, 4, and 8 weeks of treatment. Results: A total of 44 patients were included, including 16 males and 28 females, with an average age of (50.6±13.5) years. There were 21 cases in the FVR group and 23 cases in the ST-PVR group. In the ST-PVR group, DHI score (49.5±26.8 vs 61.3±21.4, P=0.046) and SAS score (39.1±7.8 vs 44.3±6.6, P=0.021) significantly improved after 2 weeks of treatment, while significant improvement occurred only after 8 weeks of treatment in the FVR group (DHI score: 28.1±15.9 vs 53.1±18.5, P=0.001; SAS score: 35.3±6.7 vs 43.1±8.4, P=0.010). There was no significant change of ABC score in the FVR group after 8 weeks of treatment (86.5±12.9 vs 83.4±18.1, P=0.373), while a significant improvement was observed in the ST-PVR group after 4 weeks of treatment (83.6±15.2 vs 78.4±15.1, P=0.015). The caloric test results showed that after 8 weeks of treatment, the proportion of patients with unilateral weakness<25% increased in both groups [FVR group: 57.1% (12/21) vs 9.5% (2/21), P=0.001; ST-PVR group: 52.2% (12/23) vs 17.4% (4/23), P=0.014]. In the ST-PVR group, the proportion of patients with dominant preference≤25% significantly increased [91.3% (21/23) vs 60.9% (14/23), P=0.016], while there was no significant change in the FVR group [61.9 (13/21) vs 57.1% (12/21), P=0.500]. The proportion of patients with SOT score≥70 in the ST-PVR group increased significantly after 2 weeks of treatment [69.6% (16/23) vs 30.4% (7/23), P=0.009], while the FVR group showed a significant increase only after 8 weeks of treatment [81.0% (17/21) vs 42.9% (9/21), P=0.012]. Conclusion: Both FVR and ST-PVR effectively promote vestibular compensation by improving objective vestibular functions and relieving subjective symptoms and anxiety of the patients with decompensation recurrent vertigo, while ST-PVR might shorten the recovery time and increase balance confidence.

[Clinical features of patients with metastatic pheochromocytoma/paraganglioma]

Objective: To analyze the clinical features of patients with metastatic pheochromocytoma/paraganglioma (PPGL). Methods: A follow-up study. The clinical data of 250 patients with metastatic PPGL treated at Peking Union Medical College Hospital from January 2018 to August 2023 were retrospectively analyzed, including 124 males and 126 females. The clinical features and treatment status of patients with metastatic PPGL were summarized and analyzed. Kaplan-Meier survival curve was used to evaluate patients' prognosis. Results: The age of onset, age of diagnosis, and age of tumor metastasis in patients with metastatic PPGL were (33.1±14.2) years, (35.4±15.2) years, and (40.7±15.3) years, respectively. Metastasis occurred in 26.4%(66/250) of patients at the time of initial diagnosis. Among patients without metastases at the time of initial diagnosis, the time from primary tumor resection to metastasis[M(Q1, Q3)] was 5.0 (3.0, 9.0) years, among which 20.1%(37/184) of patients had metastases more than 10 years after surgery. Most patients showed increased 24-hour urinary norepinephrine and plasma normetanephrine, accounting for 78.2%(176/225) and 78.7%(85/108), respectively. 42.3%(69/163) of patients had increased neuron specific enolase (NSE)levels. Germline mutations were screened in 201 patients, of which 55.2%(111/201) had germline pathogenic mutations. In patients with gene mutations, 76.5%(85/111) had SDHB mutations. 52.0%(130/250) of metastatic PPGL patients had primary sites outside the adrenal gland, with the Ki-67 index of 5% (3%, 8%). There were 85.6%(214/250) patients had multisystem metastasis, with bone metastasis being the most common site of metastasis, accounting for 60.8%(152/250). In terms of treatment, 32.8%(75/229) of patients underwent two treatment regimens and 8.7%(20/229) of patients underwent three treatment regimens. Most patients had a good prognosis, with a 5-year and 10-year survival rate of 88.0% and 84.0%, respectively. However, some patients had rapid disease progression, and as of August 2023, 30 patients died, and the time from diagnosis to death in deceased patients was 2.0 (1.0, 4.0) years. Conclusions: Patients with metastatic PPGL have a high rate of germline mutations, especially those with SDHB mutations. The metastatic PPGL is usually multisystem metastasis with the characteristics of mostly paraganglioma, large lesion diameter and high Ki-67 index.

Study of the f_{0}(980) and f_{0}(500) Scalar Mesons through the Decay D_{s}^{+}→π^{+}π^{-}e^{+}ν_{e}

Using e^{+}e^{-} collision data corresponding to an integrated luminosity of 7.33  fb^{-1} recorded by the BESIII detector at center-of-mass energies between 4.128 and 4.226 GeV, we present an analysis of the decay D_{s}^{+}→π^{+}π^{-}e^{+}ν_{e}, where the D_{s}^{+} is produced via the process e^{+}e^{-}→D_{s}^{*±}D_{s}^{∓}. We observe the f_{0}(980) in the π^{+}π^{-} system and the branching fraction of the decay D_{s}^{+}→f_{0}(980)e^{+}ν_{e} with f_{0}(980)→π^{+}π^{-} measured to be (1.72±0.13_{stat}±0.10_{syst})×10^{-3}, where the uncertainties are statistical and systematic, respectively. The dynamics of the D_{s}^{+}→f_{0}(980)e^{+}ν_{e} decay are studied with the simple pole parametrization of the hadronic form factor and the Flatté formula describing the f_{0}(980) in the differential decay rate, and the product of the form factor f_{+}^{f_{0}}(0) and the c→s Cabibbo-Kobayashi-Maskawa matrix element |V_{cs}| is determined for the first time to be f_{+}^{f_{0}}(0)|V_{cs}|=0.504±0.017_{stat}±0.035_{syst}. Furthermore, the decay D_{s}^{+}→f_{0}(500)e^{+}ν_{e} is searched for the first time but no signal is found. The upper limit on the branching fraction of D_{s}^{+}→f_{0}(500)e^{+}ν_{e}, f_{0}(500)→π^{+}π^{-} decay is set to be 3.3×10^{-4} at 90% confidence level.

Suramin inhibits phenotypic transformation of vascular smooth muscle cells and neointima hyperplasia by suppressing transforming growth factor beta receptor 1 /Smad2/3 pathway activation

Vascular smooth muscle cells (VSMCs) contribute to neointimal hyperplasia (NIH) after vascular injury, a common feature of vascular remodelling disorders. Suramin is known to exert antitumour effects by inhibiting the proliferation of various tumour cells; however, its effects and mechanism on VSMCs remain unclear. This study investigated the effects of suramin on human aortic smooth muscle cells (HASMCs), rat aortic smooth muscle cells (RASMCs) and NIH to examine its suitability for the prevention of vascular remodelling disorders. In vitro, suramin administration reduced platelet-derived growth factor type BB (PDGF-BB)-stimulated proliferation, migration, and dedifferentiation of VSMCs through a transforming growth factor beta receptor 1 (TGFBR1)/Smad2/3-dependent pathway. Suramin dramatically inhibited NIH ligation in the left common carotid artery (LCCA) vivo. Therefore, our results indicate that suramin protects against the development of pathological vascular remodelling by attenuating VSMCs proliferation, migration, and phenotypic transformation and may be used as a potential medicine for the treatment of NIH.

Temperature-Controlled Selective Formation of Silver Nanoclusters and Their Transformation to the Same Product

Herein, two atomically precise silver nanoclusters, Ag54 and Ag33, directed by inner anion templates (CrO42- and/or Cl-), are initially isolated as a mixed phase from identical reactants across a wide temperature range (20-80 °C). Interestingly, fine-tuning the reaction temperature can realize pure phase synthesis of the two nanoclusters; that is, a metastable Ag54 is kinetically formed at a low temperature (20 °C), whereas such a system is steered towards a thermodynamically stable Ag33 at a relatively high temperature (80 °C). Electrospray ionization mass spectrometry illustrates that the stability of Ag33 is superior to that of Ag54, which is further supported by density functional theory calculations. Importantly, the difference in structural stability can influence the pathway of 1,4-bis(pyrid-4-yl)benzene induced transformation reaction starting from Ag54 and Ag33. The former undergoes a dramatic breakage-reorganization process to form an Ag31 dimer (Ag31), while the same product can be also achieved from the latter following a noninvasive ligand exchange process. Both the Ag54 and Ag33 have the potential for further remote laser ignition applications. This work not only demonstrates how temperature controls the isolation of a specific phase, but also sheds light on the structural transformation pathway of nanoclusters with different stability.

GLUT4 localisation with the plasma membrane is unaffected by an increase in plasma free fatty acid availability

BACKGROUND

Insulin-stimulated glucose uptake into skeletal muscle occurs via translocation of GLUT4 from intracellular storage vesicles to the plasma membrane. Elevated free fatty acid (FFA) availability via a lipid infusion reduces glucose disposal, but this occurs in the absence of impaired proximal insulin signalling. Whether GLUT4 localisation to the plasma membrane is subsequently affected by elevated FFA availability is not known.

METHODS

Trained (n = 11) and sedentary (n = 10) individuals, matched for age, sex and body mass index, received either a 6 h lipid or glycerol infusion in the setting of a concurrent hyperinsulinaemic-euglycaemic clamp. Sequential muscle biopsies (0, 2 and 6 h) were analysed for GLUT4 membrane localisation and microvesicle size and distribution using immunofluorescence microscopy.

RESULTS

At baseline, trained individuals had more small GLUT4 spots at the plasma membrane, whereas sedentary individuals had larger GLUT4 spots. GLUT4 localisation with the plasma membrane increased at 2 h (P = 0.04) of the hyperinsulinemic-euglycemic clamp, and remained elevated until 6 h, with no differences between groups or infusion type. The number of GLUT4 spots was unchanged at 2 h of infusion. However, from 2 to 6 h there was a decrease in the number of small GLUT4 spots at the plasma membrane (P = 0.047), with no differences between groups or infusion type.

CONCLUSION

GLUT4 localisation with the plasma membrane increases during a hyperinsulinemic-euglycemic clamp, but this is not altered by elevated FFA availability. GLUT4 appears to disperse from small GLUT4 clusters located at the plasma membrane to support glucose uptake during a hyperinsulinaemic-euglycaemic clamp.

mRNA Sonotransfection of Tumors with Polymeric Microbubbles: Co-Formulation versus Co-Administration

Despite its high potential, non-viral gene therapy of cancer remains challenging due to inefficient nucleic acid delivery. Ultrasound (US) with microbubbles (MB) can open biological barriers and thus improve DNA and mRNA passage. Polymeric MB are an interesting alternative to clinically used lipid-coated MB because of their high stability, narrow size distribution, and easy functionalization. However, besides choosing the ideal MB, it remains unclear whether nanocarrier-encapsulated mRNA should be administered separately (co-administration) or conjugated to MB (co-formulation). Therefore, the impact of poly(n-butyl cyanoacrylate) MB co-administration with mRNA-DOTAP/DOPE lipoplexes or their co-formulation on the transfection of cancer cells in vitro and in vivo is analyzed. Sonotransfection improved mRNA delivery into 4T1 breast cancer cells in vitro with co-administration being more efficient than co-formulation. In vivo, the co-administration sonotransfection approach also resulted in higher transfection efficiency and reached deeper into the tumor tissue. On the contrary, co-formulation mainly promoted transfection of endothelial and perivascular cells. Furthermore, the co-formulation approach is much more dependent on the US trigger, resulting in significantly lower off-site transfection. Thus, the findings indicate that the choice of co-administration or co-formulation in sonotransfection should depend on the targeted cell population, tolerable off-site transfection, and the therapeutic purpose.

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.

The value of quantitative contrast-enhanced ultrasonography analysis in evaluating central retinal artery microcirculation in patients with diabetes mellitus: comparison with colour Doppler imaging

AIM

To compare the efficacy of quantitative contrast-enhanced ultrasonography (CEUS) analysis and colour Doppler ultrasound (CDU) in evaluating central retinal artery (CRA) microcirculation in patients with diabetes mellitus (DM).

MATERIALS AND METHODS

In this prospective study, a total of 55 patients (98 eyes) with DM were enrolled as the study group. They were compared to 46 age-matched healthy volunteers (92 eyes) who were selected as the control group. Each patient underwent CDU and subsequent CEUS examination. CDU and quantitative CEUS parameters were evaluated. The diagnostic efficiency of the diagnostic performance of CEUS and CDU was evaluated and compared, and the scale thresholds of predictive indicators for the diagnosis of proliferative diabetic retinopathy (PDR) were evaluated using receiver operating characteristics (ROC) curve analyses.

RESULTS

Group pairwise comparisons showed that the end diastolic velocity (EDV) and arrival time (AT) of CRA were significant predictors for PDR by CDU and by quantitative CEUS analysis, respectively (all p<0.05). The ROC curve analysis showed that the area under the curve value of AT was significantly higher than that of EDV (0.875 versus 0.634, p=0.0002). Accordingly, an AT cut-off value of 1.07 seconds resulted a sensitivity of 90.62 % and a specificity of 79.31 %.

CONCLUSION

Quantitative CEUS analysis can improve the accuracy of clinical staging of diabetic retinopathy for the patients with DM, and the AT showed the best diagnostic efficiency.

The safety signal detection and analysis of monoclonal antibodies against SARS-CoV-2 based on real-world evidence - the suitable selectivity for different populations

OBJECTIVE

Bebtelovimab (BEB), Tixagevimab/Cilgavimab (TIX/CIL), and Sotrovimab (SOT) are important agents against the severe acute respiratory syndrome coronavirus 2-Omicron strain. However, due to their short duration of application, little is known about their safety profiles. This research aimed to explore the safety profile of these monoclonal antibodies (mAbs) via real-world evidence databases and data mining tools.

MATERIALS AND METHODS

Safety reports were retrieved from the database of the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System from April 2022 to March 2023. To detect the safety signal, the disproportionality analysis was performed using the reporting odds ratio method.

RESULTS

SOT had the greatest proportion of "skin and subcutaneous tissue disorders" and "disorders of investigations"; BEB showed significant associations with "gastrointestinal disorders" and "nervous system disorders"; TIX/CIL had the weakest correlation with "skin and subcutaneous tissue disorders" and "general disorders and administration site conditions". Furthermore, there were still other signals related to nervous system disorders, gastrointestinal disorders only caused by BEB. TIX/CIL has been reported solely to be associated with multiple types of cardiovascular disorders. As for SOT alone, signals were strongly related to infusion reactions and hypersensitivity.

CONCLUSIONS

In summary, SOT may be unsuitable for allergic patients and may lead to abnormal test results. BEB showed the highest correlations with gastrointestinal and neuropsychiatric events. In addition, its infusion reactions should also be noted. TIX/CIL can lead to a variety of cardiovascular events.

Blockade of BLyS inhibits B-cell responses and antibody production for the prevention of chronic transplant rejection

BACKGROUND

Chronic rejection, closely related to the activation of B cells and donor-specific antibody (DSA) production, has unsatisfactory therapeutic outcomes. B lymphocyte stimulator (BLyS) is a major regulatory factor that controls the activation and differentiation of B cells. However, it remains unclear whether BLyS blockade can regulate B and plasma cells in the transplantation setting and affect chronic rejection. Here, we investigated the efficacy of the BLyS inhibitors belimumab and telitacicept in controlling B-cell response and preventing chronic rejection.

METHODS

The effects of belimumab and telitacicept on B-cell activation, differentiation, and antibody production in vitro were determined. A chronic rejection model in mouse was established by allogeneic cardiac transplantation with CTLA4-Ig treatment. Allograft survival, histology, DSA levels, and B-cell responses were analyzed to evaluate the chronic rejection-preventive effects of belimumab and telitacicept.

RESULTS

In vitro experiments confirmed that belimumab and telitacicept inhibited B-cell activation and differentiation and reduced antibody production. In vivo experiments indicated that they significantly prolonged allograft survival, attenuated chronic rejection through significant suppression of myocardial ischemic necrosis and interstitial fibrosis, and reduced DSA-IgG levels, C4d deposition, and inflammatory cell infiltration. Furthermore, the frequencies of B cells, plasma cells, and IgG-producing cells in the recipients' spleen, lymph nodes, bone marrow, and blood were decreased after BLyS inhibitors treatment.

CONCLUSIONS

This study demonstrated that belimumab and telitacicept inhibit B-cell responses and antibody production and alleviate chronic transplant rejection. Therefore, BLyS inhibitors are expected to be used for the prevention of chronic rejection in clinical practice.

Sporisorium reilianum polysaccharides improve DSS-induced ulcerative colitis by regulating intestinal barrier function and metabolites

This study investigated the regulatory effects of Sporisorium reilianum polysaccharides (SRPS) on metabolism and the intestinal barrier in mice with colitis induced by dextran sulfate sodium (DSS). SRPS were resistant to the digestion of saliva, gastric juices, and intestinal fluid. SRPS significantly reduced the disease activity index and inhibited DSS-induced colon shortening. The expression of proinflammatory cytokines in the colon was normal (P < 0.05). Acetic acid, propionic acid, butyric acid, isobutyric acid, and isovaleric acid contents increased. Moreover, 64 biomarker metabolites were affected, including 42 abnormal decreases and 22 abnormal increases caused by DSS, which targeted amino acid biosynthesis; tryptophan metabolism; protein digestion and absorption; aminoacyl-tRNA biosynthesis; and glycine, serine, and threonine metabolism. In addition, SRPS reduced goblet cell loss and increased mucin secretion. The short-chain fatty acid receptor GPR41 was activated, and zonula occludens-1 and occludin expression levels were upregulated. Epithelial cell apoptosis was inhibited by increased Bcl-2 and decreased Bax expression NLRP3, ASC, and caspase-1 protein levels decreased. Intestinal barrier damage improved, and colon inflammation was reduced. Thus, our preliminary findings reveal that SRPS regulates metabolism and has the potential to protect the intestinal barrier in ulcerative colitis mice.

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.

Achromobacter species (sp.) outbreak caused by hospital equipment containing contaminated water: risk factors for infection

BACKGROUND

Nosocomial outbreaks of urinary tract infections caused by Achromobacter spp. have been rare in recent decades.

AIM

To identify the origin of an Achromobacter sp. outbreak, conduct multi-modal infection control measures, and finally to stop the outbreak. To this end, an epidemiological outbreak investigation and risk factor analysis were performed.

METHODS

Achromobacter sp. was detected in 22 patients in our urology wards and six environmental cultures of specimens obtained from the operating rooms. Strains isolated were submitted for antimicrobial susceptibility testing. An on-site epidemiological investigation, evaluation of patient medical records, and environmental sampling were performed to identify the source of the outbreak, and implementation of infection control intervention. A case-control study was performed to analyse the potential risk factors.

FINDINGS

Environmental sampling showed that the source of the infection for 22 patients was an ISA-IIIA-type medical pressurizer containing contaminated water. A case-control analysis showed that the risk factors for infection were: diagnosis of kidney/ureteral stones, surgery, placement of a double-J stent, and history of hospitalization in the past three months.

CONCLUSION

It was concluded that the outbreak occurred in patients who underwent internal lithotripsy and double-J stent placement, due to contact transmission with the contaminated sensor and connecting tubes of the ISA-IIIA-type medical pressurizer.

Chelerythrine induces apoptosis and ferroptosis through Nrf2 in ovarian cancer cells

Ovarian cancer is a prevalent malignancy in the female reproductive system, representing a significantly fatal and incurable tumor. Chelerythrine (CHE), a natural benzopyridine alkaloid, has demonstrated a broad spectrum of anticancer activities. Nevertheless, the ovarian cancer inhibitory impact of CHE remains unclear. In this study, we investigated the cytotoxic mechanism and potential targets of CHE on in vitro cultures of A2780 and SKOV3 cells derived from ovarian cancer. Additionally, in vivo experiments were conducted to confirm the suppressive impact of CHE on tumor growth in nude mice. The findings revealed that CHE impeded the growth of A2780 and SKOV3 cells in a concentration-time-dependent manner and significantly suppressed the development of tumors in nude mice. CHE elevated the level of oxidative stress in tumor cells, prompted cell cycle halt in the S phase, and increased their mitochondrial membrane potential. Western blotting results demonstrated that CHE could modulate the expression of proteins associated with apoptotic and ferroptosis processes in A2780 and SKOV3 cells. Nrf2 was verified to be an upstream key target mediating the inhibitory impact of CHE on ovarian cancer cells. In summary, CHE exerts its anti-cancer effects on ovarian cancer by modulating Nrf2, inhibiting cellular proliferation, and promoting apoptosis and ferroptosis.

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.

Realizing Synthetic Dimensions and Artificial Magnetic Flux in a Trapped-Ion Quantum Simulator

Synthetic dimension is a potent tool in quantum simulation of topological phases of matter. Here we propose and demonstrate a scheme to simulate an anisotropic Harper-Hofstadter model with controllable magnetic flux on a two-leg ladder using the spin and motional states of a single trapped ion. We verify the successful simulation of this model by comparing the measured dynamics with theoretical predictions under various coupling strength and magnetic flux, and we observe the chiral motion of wave packets on the ladder as evidence of the topological chiral edge modes. We develop a quench path to adiabatically prepare the ground states for varying magnetic flux and coupling strength, and we measure the chiral current on the ladder for the prepared ground states, which allows us to probe the quantum phase transition between the Meissner phase and the vortex phase. Our work demonstrates the trapped ion as a powerful quantum simulation platform for topological quantum matter.

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

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

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Affiliation(s)

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

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

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

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

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

[Investigation of Anisakis infections in coastal marine fishes and awareness of anisakiasis control knowledge among residents in Yantai City in 2021]

OBJECTIVE

To investigate the prevalence of Anisakis infections in coastal marine fishes and awareness of anisakiasis control knowledge among local residents in Yantai City, Shandong Province in 2021, so as to provide insights into formulation of anisakiasis control interventions.

METHODS

Marine fishes were purchased from Shunxin Port, Yantai City, Shandong Province in November 2021, and the presence of Anisakis was detected in different species of fishes and different fish sites. The correlations between body length and weight of marine fish and intensity of Anisakis infections were examined using Spearman's rank correlation analysis, and the dietary habits and anisakiasis control knowledge were investigated using questionnaire surveys among local residents.

RESULTS

A total of 201 marine fishes belonging to 20 species were dissected, and Anisakis was detected in 77 marine fishes (38.31%) belonging to 11 species (55.00%), with a mean infection intensity of 45.04 parasites per fish (3 468/77). Spearman's rank correlation analysis revealed that the body length (rs = 0.74, P < 0.05) and weight (rs = 0.79, P < 0.01) of the monkfish correlated positively with the intensity of Anisakis infections, and the body length (rs = 0.68, P < 0.05) of the flatfish correlated positively with the intensity of Anisakis infections, while no correlations were examined between the body length or weight of other marine fishes and the intensity of Anisakis infections. Of all respondents, 53.38% men and 56.67% women did not know anisakiasis control knowledge at all, and there was a significant difference in the proportion of respondents using separate chopping boards for raw and cooked food from different villages (χ2 = 17.89, P < 0.01), while there was an age-specific proportion of respondents with habitats of eating raw or semi-raw seafood (χ2 = 28.27, P < 0.01).

CONCLUSIONS

The prevalence and intensity of Anisakis infections were high in coastal marine fishes in Yantai City in 2021, and the awareness of anisakiasis control knowledge was low among local residents. Intensified health education pertaining to anisakiasis control knowledge is recommended to reduce the risk of Anisakis infections.

Revelation of adhesive proteins affecting cellular contractility through reference-free traction force microscopy

Over the past few decades, the critical role played by cellular contractility associated mechanotransduction in the regulation of cell functions has been revealed. In this case, numerous biomaterials have been chemically or structurally designed to manipulate cell behaviors through the regulation of cellular contractility. In particular, adhesive proteins including fibronectin, poly-L-lysine and collagen type I have been widely applied in various biomaterials to improve cell adhesion. Therefore, clarifying the effects of adhesive proteins on cellular contractility has been valuable for the development of biomaterial design. In this study, reference-free traction force microscopy with a well-organized microdot array was designed and prepared to investigate the relationship between adhesive proteins, cellular contractility, and mechanotransduction. The results showed that fibronectin and collagen type I were able to promote the assembly of focal adhesions and further enhance cellular contraction and YAP activity. In contrast, although poly-L-lysine supported cell spreading and elongation, it was inefficient at inducing cell contractility and activating YAP. Additionally, compared with cellular morphogenesis, cellular contraction was essential for YAP activation.

[Mid-term efficacy evaluation of ABO incompatible living relative kidney transplantation based on protocol biopsy]

Objective: To evaluate the mid-term efficacy of ABO incompatible living donor kidney transplantation (ABOi-KT) based on the results of routine renal biopsy for transplantation. Methods: Retrospective collection of clinical data from 23 pairs of ABOi-KT donors and recipients at the First Affiliated Hospital of Sun Yat-sen University from July 2015 to November 2021. ABOi-KT was performed on recipients after desensitization treatment, and the results of routine kidney transplant biopsy at 1 week, 1 month, 3 months, 6 months, and 12 months after surgery were analyzed. Combined with blood type antibody levels and renal function recovery, the mid-term efficacy of ABOi-KT was evaluated. Results: Among the 23 recipients, there were 19 males and 4 females; age range from 19 to 47 years old [(29.6±6.7) years old], all underwent ABOi-KT successfully after receiving desensitization treatment. The follow-up time was (44.6±22.4) months, of which 22 cases were followed up for more than 1 year. The incidence rates of rejection reactions at 1 week, 1 month, 3 months, 6 months, and 12 months after surgery were 15.0% (3/20), 11.1% (1/9), 7.7% (1/13), 25.0% (3/12), and 12.5% (1/8), respectively. For receptors with rejection reactions, targeted anti-rejection therapy was performed based on clinical symptoms and various indicators. Borderline T cell mediated rejection (TCMR) can be converted to mild tubular inflammation after anti-rejection treatment. The positive rate of complement C4d in peritubular capillaries was 95.0% (19/20) one week after surgery, and the positive rate of complement C4d was 100% at 3 and 12 months after surgery. The cumulative survival rates at 1, 3, 5, and 7 years after surgery were all 100%. The cumulative survival rates at 1, 3, 5, and 7 years after kidney transplantation were 100%, 93.3%, 84.0%, and 84.0%, respectively. Except for 2 recipients who underwent transplantation in 2017 and experienced kidney failure at 30 and 49 months after surgery, all other transplanted kidneys survived. Conclusions: The results of routine renal transplant biopsy show that ABOi-KT has a good mid-term therapeutic effect. The pathological changes of ABOi-KT can be dynamically observed through routine renal transplant biopsy and targeted treatment for rejection reactions can be provided accordingly.

[Multicenter evaluation of minimal residual disease monitoring in early induction therapy for treatment of childhood acute lymphoblastic leukemia]

Objective: To evaluate the role of minimal residual disease (MRD) monitoring during early induction therapy for the treatment of childhood acute lymphoblastic leukemia (ALL). Methods: This was a multicenter retrospective cohort study. Clinical data of 1 164 ALL patients first diagnosed between October 2016 and June 2019 was collected from 16 hospitals in South China Children's Leukemia Group. According to MRD assay on day 15 of early induction therapy, they were divided into MRD<0.10% group, MRD 0.10%-<10.00% group and MRD≥10.00% group. According to MRD assay on day 33, they were divided into MRD<0.01% group, MRD 0.01%-<1.00% group and MRD≥1.00% group. Age, onset white blood cell count, central nervous system leukemia (CNSL), molecular genetic characteristics and other data were compared between groups. Kaplan-Meier method was used for survival analysis. Cox regression model was used to analyze prognostic factors. Results: Of the 1 164 enrolled patients, there were 692 males and 472 females. The age of diagnosis was 4.7 (0.5, 17.4) years. The white blood cell count at initial diagnosis was 10.7 (0.4, 1 409.0) ×109/L. Among all patients, 53 cases (4.6%) had CNSL. The follow-up time was 47.6 (0.5, 68.8) months. The 5-year overall survival (OS) and 5-year relapse-free survival (RFS) rates were (93.1±0.8) % and (90.3±1.1) %. On day 15 of early induction therapy, there were 466 cases in the MRD<0.10% group, 523 cases in the MRD 0.10%-<10.00% group and 175 cases in the MRD≥10.00% group. The 5-year OS rates of the MRD<0.10% group, MRD 0.10%-<10.00% group and MRD≥10.00% group were (95.4±1.0) %, (93.3±1.1) %, (85.4±2.9) %, respectively, while the RFS rates were (93.2±1.6) %, (90.8±1.4) %, (78.9±4.3) %, respectively (χ2=16.47, 21.06, both P<0.05). On day 33 of early induction therapy, there were 925 cases in the MRD <0.01% group, 164 cases in the MRD 0.01%-<1.00% group and 59 cases in the MRD≥1.00% group. The 5-year RFS rates in the MRD 0.01%-<1.00% group was lowest among three groups ((91.4±1.2) % vs. (84.5±3.2) % vs. (87.9±5.1) %). The difference between three groups is statistically significant (χ2=9.11, P=0.010). Among ALL patients with MRD≥10.00% on day 15 of induction therapy, there were 80 cases in the MRD <0.01% group on day 33, 45 cases in the MRD 0.01%-<1.00% group on day 33 and 45 cases in the MRD≥1.00% group on day 33. The 5-year RFS rates of three groups were (83.9±6.0)%, (67.1±8.2)%, (83.3±6.9)% respectively (χ2=6.90, P=0.032). Univariate analysis was performed in the MRD≥10.00% group on day 15 and the MRD 0.01%-<1.00% group on day 33.The 5-year RFS rate of children with CNSL was significantly lower than that without CNSL in the MRD≥10.00% group on day 15 ((50.0±20.4)% vs. (80.3±4.4)%,χ2=4.13,P=0.042). Patients with CNSL or MLL gene rearrangement in the MRD 0.01%-<1.00% group on day 33 had significant lower 5-year RFS rate compared to those without CNSL or MLL gene rearrangement ((50.0±25.0)% vs. (85.5±3.1)%,χ2=4.06,P=0.044;(58.3±18.6)% vs. (85.7±3.2)%,χ2=9.44,P=0.002). Multivariate analysis showed that age (OR=0.58, 95%CI 0.35-0.97) and white blood cell count at first diagnosis (OR=0.43, 95%CI 0.27-0.70) were independent risk factors for OS. The MRD level on day 15 (OR=0.55,95%CI 0.31-0.97), ETV6-RUNX1 fusion gene (OR=0.13,95%CI 0.03-0.54), MLL gene rearrangement (OR=2.55,95%CI 1.18-5.53) and white blood cell count at initial diagnosis (OR=0.52,95%CI 0.33-0.81) were independent prognostic factors for RFS. Conclusions: The higher the level of MRD in early induction therapy, the worse the OS. The MRD levels on day 15 is an independent prognostic factor for RFS.The MRD in early induction therapy guided accurate risk stratification and individualized treatment can improve the survival rate of pediatric ALL.