Multiscale calculations reveal new insights into the reaction mechanism between KRASG12C and α, β-unsaturated carbonyl of covalent inhibitors

Utilizing α,β-unsaturated carbonyl group as Michael acceptors to react with thiols represents a successful strategy for developing KRASG12C inhibitors. Despite this, the precise reaction mechanism between KRASG12C and covalent inhibitors remains a subject of debate, primarily due to the absence of an appropriate residue capable of deprotonating the cysteine thiol as a base. To uncover this reaction mechanism, we first discussed the chemical reaction mechanism in solvent conditions via density functional theory (DFT) calculation. Based on this, we then proposed and validated the enzymatic reaction mechanism by employing quantum mechanics/molecular mechanics (QM/MM) calculation. Our QM/MM analysis suggests that, in biological conditions, proton transfer and nucleophilic addition may proceed through a concerted process to form an enolate intermediate, bypassing the need for a base catalyst. This proposed mechanism differs from previous findings. Following the formation of the enolate intermediate, solvent-assisted tautomerization results in the final product. Our calculations indicate that solvent-assisted tautomerization is the rate-limiting step in the catalytic cycle under biological conditions. On the basis of this reaction mechanism, the calculated kinact/ki for two inhibitors is consistent well with the experimental results. Our findings provide new insights into the reaction mechanism between the cysteine of KRASG12C and the covalent inhibitors and may provide valuable information for designing effective covalent inhibitors targeting KRASG12C and other similar targets.

Porphyrin fluorescence imaging for real-time monitoring and visualization of the freshness of beef stored at different temperatures

This study presents a novel fluorescence imaging method for the real-time monitoring of beef quality deterioration and freshness. The fluorescence property of porphyrin in the form of heme can be used to characterize quality changes in beef during storage. Therefore, a fluorescence imaging system with an excitation light source of 440 nm and a CCD camera with a specific wavelength filter of 595 nm was constructed, and the porphyrin fluorescence images of beef samples stored at different temperatures were then collected. The quantitative model for predicting the microbial freshness indicator (TVC) of beef was built with the support vector machine regression (SVR) algorithm and produced satisfactory results with Rc2 and Rp2 of 0.858 and 0.812, respectively. The classification model based on the support vector machine (SVM) algorithm classified beef freshness into "fresh" and "spoiled", with calibration and prediction accuracy of 100 % and 90.9 %, respectively.

CT quantification of pulmonary vessels in lung aging

AIM

To evaluate the effect of aging on pulmonary vessels based on computed tomography (CT) quantification and analyse the correlation between quantitative pulmonary vascular volume and pulmonary function during aging.

MATERIALS AND METHODS

A total of 330 healthy adult volunteers, including 161 men (53 aged 20-39 years, 61 aged 40-59 years, and 47 aged ≥60 years) and 169 women (53 aged 20-39 years, 63 aged 40-59 years, and 53 aged ≥60 years) were recruited in this study. AVIEW software was used to quantitatively measure pulmonary vascular volume, including pulmonary total blood vessel volume (TBV) and small blood vessel volume with a cross-sectional area of <5 mm2 (BV5). Pulmonary vascular volume parameters were standardised using the ratio of vascular volume to the body surface area (BSA; TBV/BSA and BV5/BSA). Subsequently, the effect of aging on the pulmonary vessels was analysed.

RESULTS

The pulmonary vascular volume parameters TBV/BSA and BV5/BSA of the whole lung, right lung, and left lung decreased significantly with increasing age (p<0.05). Additionally, TBV/BSA and BV5/BSA of the whole lung were higher in men than in women. The declining trend of pulmonary vascular volume was consistent in men and women and increased with age.

CONCLUSIONS

The pulmonary vascular volume parameters, TBV/BSA and BV5/BSA, decreased with age and were weakly positively correlated with pulmonary function.

Association between serum triglyceride level and severity of acute biliary pancreatitis

BACKGROUND

Acute biliary pancreatitis (ABP) is the most common type of acute pancreatitis. However, the effect of serum triglyceride (TG) levels on the severity of ABP remains unclear. The aim of this study was to assess the correlation between serum TG levels and the severity of ABP.

METHODS

Data from 526 ABP patients was analyzed in this study. The patients were divided into normal and elevated groups according to the TG level measured within 24 h after admission, and the elevated group was further divided into mild, moderate, and severe elevated groups. The demographic data and clinical outcomes of each group were compared.

RESULTS

Of the 526 ABP patients, 394 were in the normal TG group and 132 were in the elevated TG group (36 mild, 57 moderate, and 39 severe). The elevated group was younger (51.5 ± 12.9 vs. 58.9 ± 13.9), predominantly male (66.7% vs. 45.2%), had more history of diabetes (22.7% vs. 12.4%) and hyperlipidemia (19.7% vs. 0.8%), and developed systemic inflammatory response syndrome (SIRS) (25.8% vs. 15.5%), persistent organ failure (POF) (11.4% vs. 2.8%), and local complications (62.9% vs. 42.1%) more frequently compared to the normal group (P < 0.05). The incidence of SIRS, POF, acute peripancreatic fluid collection (APFC), and acute necrotic collection (ANC) increased with increasing TG levels (Ptrend < 0.05). In multivariate analysis, TG was independently associated with POF, APFC, and ANC in increments of 100 mg/dl (P < 0.05), and there was a linear relationship between TG levels and POF, APFC, and ANC (non-linear P > 0.05, P overall <0.05). In addition, nonalcoholic fatty liver disease is not a risk factor for POF, ANC, and APFC in ABP patients.

CONCLUSIONS

Elevated serum TG levels were independently associated with more severe ABP. The incidence of POF, APFC, and ANC in ABP patients increased with the increase of TG levels, with a linear relationship.

PTGS2: A potential immune regulator and therapeutic target for chronic spontaneous urticaria

AIMS

Chronic spontaneous urticaria (CSU) is a common and debilitating skin disease that is difficult to control with existing treatments, and the pathogenesis of CSU has not been fully revealed. The aim of this study was to explore the underlying mechanisms of CSU and identify potential treatments.

MATERIALS AND METHODS

Microarray datasets of CSU were obtained from Gene Expression Omnibus database. Differentially expressed genes between skin lesions of CSU and normal controls (LNS-DEGs) were identified, and the enrichment analyses of LNS-DEGs were performed. Hub genes of LNS-DEGs were selected by protein-protein interaction analysis. The co-expression and transcriptional regulatory networks of hub genes were conducted using GeneMANIA and TRRUST database, respectively. CIBERSORT was utilized for immune cell infiltration analysis. Experimental validation was performed by β-hexosaminidase release examination and passive cutaneous anaphylaxis (PCA) mouse model.

KEY FINDINGS

A total of 247 LNS-DEGs were identified, which were enriched in cell migration, cell chemotaxis, and inflammatory pathways such as TNF and interleukin (IL) -17 signaling pathway. Among LNS-DEGs, seven upregulated (PTGS2, CCL2, IL1B, CXCL1, IL6, VCAM1, ICAM1) and one downregulated hub gene (PECAM1) were selected. Immune infiltration analysis identified eight different immune cells, such as activated/resting mast cells and neutrophils. Furthermore, PTGS2, encoding cyclooxygenase 2 (COX2), was selected for further validation. COX2 inhibitor, celecoxib, significantly inhibited mast cell degranulation, and reduced vascular permeability and inflammatory cytokine expression in PCA mouse model.

SIGNIFICANCE

PTGS2 may be a potential regulator of immunity and inflammation in CSU. Targeting PTGS2 is a new perspective for CSU treatment.

Identity-Guided Collaborative Learning for Cloth-Changing Person Reidentification

Cloth-changing person reidentification (ReID) is a newly emerging research topic aimed at addressing the issues of large feature variations due to cloth-changing and pedestrian view/pose changes. Although significant progress has been achieved by introducing extra information (e.g., human contour sketching information, human body keypoints, and 3D human information), cloth-changing person ReID remains challenging because pedestrian appearance representations can change at any time. Moreover, human semantic information and pedestrian identity information are not fully explored. To solve these issues, we propose a novel identity-guided collaborative learning scheme (IGCL) for cloth-changing person ReID, where the human semantic is effectively utilized and the identity is unchangeable to guide collaborative learning. First, we design a novel clothing attention degradation stream to reasonably reduce the interference caused by clothing information where clothing attention and mid-level collaborative learning are employed. Second, we propose a human semantic attention and body jigsaw stream to highlight the human semantic information and simulate different poses of the same identity. In this way, the extraction features not only focus on human semantic information that is unrelated to the background but are also suitable for pedestrian pose variations. Moreover, a pedestrian identity enhancement stream is proposed to enhance the identity importance and extract more favorable identity robust features. Most importantly, all these streams are jointly explored in an end-to-end unified framework, and the identity is utilized to guide the optimization. Extensive experiments on six public clothing person ReID datasets (LaST, LTCC, PRCC, NKUP, Celeb-reID-light, and VC-Clothes) demonstrate the superiority of the IGCL method. It outperforms existing methods on multiple datasets, and the extracted features have stronger representation and discrimination ability and are weakly correlated with clothing.

Clinical role of the long non‑coding RNA, EGFR‑AS1, in patients with cancer: A systematic review and meta‑analysis

The novel long non-coding RNA, EGFR-AS1, is expressed in various types of solid tumour, and its oncogenic role has been fully identified. In the present study, several articles were screened following an electronic search of the PubMed database. In total, 8 studies were included in the present systematic review. For each analysis indicator risk ratios (RRs) with 95% confidence intervals (CIs) or hazard ratios (HRs) with standard errors and 95% CIs were estimated using Review Manager 5.3. The pooled RR of high EGFR-AS1 expression among patients with or without vascular invasion was 1.81 with a 95% CI of 1.22-2.69; the pooled HR of high EGFR-AS1 expression for patient overall survival rate was 1.74 with a 95% CI of 1.39-2.18. Therefore, EGFR-AS1 was identified as an oncogene and the upregulated EGFR-AS1 expression was significantly associated with advanced tumour progression and poor prognosis.

The CBS/H2S signalling pathway regulated by the carbon repressor CreA promotes cellulose utilization in Ganoderma lucidum

Cellulose is an important abundant renewable resource on Earth, and the microbial cellulose utilization mechanism has attracted extensive attention. Recently, some signalling molecules have been found to regulate cellulose utilization and the discovery of underlying signals has recently attracted extensive attention. In this paper, we found that the hydrogen sulfide (H2S) concentration under cellulose culture condition increased to approximately 2.3-fold compared with that under glucose culture condition in Ganoderma lucidum. Further evidence shown that cellulase activities of G. lucidum were improved by 18.2-27.6% through increasing H2S concentration. Then, we observed that the carbon repressor CreA inhibited H2S biosynthesis in G. lucidum by binding to the promoter of cbs, a key gene for H2S biosynthesis, at "CTGGGG". In our study, we reported for the first time that H2S increased the cellulose utilization in G. lucidum, and analyzed the mechanism of H2S biosynthesis induced by cellulose. This study not only enriches the understanding of the microbial cellulose utilization mechanism but also provides a reference for the analysis of the physiological function of H2S signals.

Circ_0044235 regulates the development of osteoarthritis by the modulation of miR-375/PIK3R3 axis

BACKGROUND

Circular RNAs (circRNAs) play an important role in osteoarthritis (OA). However, the role of circRNA in OA is still unclear. Here, we explored the role and mechanism of circ_0044235 in OA.

METHODS

CHON-001 cells were treated with IL-1β to establish OA model in vitro. The levels of circ_0044235, miR-375 and phosphoinositide 3-kinase (PI3K) regulatory subunit 3 (PIK3R3) were detected by quantitative real-time PCR. Cell count kit-8 assay and flow cytometry assay were used to detect cell viability and apoptosis. The concentrations of inflammation factors were determined by enzyme-linked immunosorbent assay. Western blot was used to detect protein levels. The interaction between miR-375 and circ_0044235 or PIK3R3 was analyzed by dual-luciferase reporter assay and RNA immunoprecipitation assay.

RESULTS

Circ_0044235 was significantly decreased in OA cartilage tissue and IL-1β-treated CHON-001 cells. Overexpression of circ_0044235 promoted IL-1β-stimulated CHON-001 cell viability and inhibited apoptosis, inflammation, and extracellular matrix (ECM) degradation. In mechanism analysis, circ_0044235 could act as a sponge for miR-375 and positively regulate PIK3R3 expression. In addition, miR-375 ameliorated the effect of circ_0044235 overexpression on IL-1β-mediated CHON-001 cells injury. In addition, miR-375 inhibition mitigated IL-1β-induced CHON-001 cell injury, while PIK3R3 silencing restored the effect.

CONCLUSION

Circ_0044235 knockdown alleviated IL-1β-induced chondrocytes injury by regulating miR-375/PIK3R3 axis, confirming that circ_0044235 might be a potential target for OA treatment.

Hybridizing carbonate and ether at molecular scales for high-energy and high-safety lithium metal batteries

Commonly-used ether and carbonate electrolytes show distinct advantages in active lithium-metal anode and high-voltage cathode, respectively. While these complementary characteristics hold promise for energy-dense lithium metal batteries, such synergy cannot be realized solely through physical blending. Herein, a linear functionalized solvent, bis(2-methoxyethyl) carbonate (BMC), is conceived by intramolecularly hybridizing ethers and carbonates. The integration of the electron-donating ether group with the electron-withdrawing carbonate group can rationalizes the charge distribution, imparting BMC with notable oxidative/reductive stability and relatively weak solvation ability. Furthermore, BMC also offers advantages including the ability to slightly dissolve LiNO3, excellent thermostability and nonflammability. Consequently, the optimized BMC-based electrolyte, even with typical concentrations in the single solvent, demonstrates high-voltage tolerance (4.4 V) and impressive Li plating/stripping Coulombic efficiency (99.4%). Moreover, it fulfills practical lithium metal batteries with satisfactory cycling performance and exceptional tolerance towards thermal/mechanical abuse, showcasing its suitability for safe high-energy lithium metal batteries.

Air-Promoted Light-Driven Hydrogen Production from Bioethanol over Core/Shell Cr2O3@GaN Nanoarchitecture

Light-driven hydrogen production from biomass derivatives offers a path towards carbon neutrality. It is often however operated with the limitations of sluggish kinetics and severe coking. Herein, a disruptive air-promoted strategy is explored for efficient and durable light-driven hydrogen production from ethanol over a core/shell Cr2O3@GaN nanoarchitecture. The correlative computational and experimental investigations show ethanol is energetically favorable to be adsorbed on the Cr2O3@GaN interface, followed by dehydrogenation toward acetaldehyde and protons by photoexcited holes. The released protons are then consumed for H2 evolution by photogenerated electrons. Afterward, O2 can be evolved into active oxygen species and promote the deprotonation and C-C cleavage of the key C2 intermediate, thus significantly lowering the reaction energy barrier of hydrogen evolution and removing the carbon residual with inhibited overoxidation. Consequently, hydrogen is produced at a high rate of 76.9 mole H2 per gram Cr2O3@GaN per hour by only feeding ethanol, air, and light, leading to the achievement of a turnover number of 266,943,000 mole H2 per mole Cr2O3 over a long-term operation of 180 hours. Notably, an unprecedented light-to-hydrogen efficiency of 17.6 % is achieved under concentrated light illumination. The simultaneous generation of aldehyde from ethanol dehydrogenation enables the process more economically promising.

A New Preparation Method of Covalent Annular Nanodiscs Based on MTGase

The preservation of the native conformation and functionality of membrane proteins has posed considerable challenges. While detergents and liposome reconstitution have been traditional approaches, nanodiscs (NDs) offer a promising solution by embedding membrane proteins in phospholipids encircled by an amphipathic helical protein MSP belt. Nevertheless, a drawback of commonly used NDs is their limited homogeneity and stability. In this study, we present a novel approach to construct covalent annular nanodiscs (cNDs) by leveraging microbial transglutaminase (MTGase) to catalyze isopeptide bond formation between the side chains of terminal amino acids, specifically Lysine (K) and Glutamine (Q). This methodology significantly enhances the homogeneity and stability of NDs. Characterization of cNDs and the assembly of membrane proteins within them validate the successful reconstitution of membrane proteins with improved homogeneity and stability. Our findings suggest that cNDs represent a more suitable tool for investigating interactions between membrane proteins and lipids, as well as for analyzing membrane protein structures.

Satellite NO2 Retrieval Complicated by Aerosol Composition over Global Urban Agglomerations: Seasonal Variations and Long-Term Trends (2001-2018)

Tropospheric nitrogen dioxide (NO2) poses a serious threat to the environmental quality and public health. Satellite NO2 observations have been continuously used to monitor NO2 variations and improve model performances. However, the accuracy of satellite NO2 retrieval depends on the knowledge of aerosol optical properties, in particular for urban agglomerations accompanied by significant changes in aerosol characteristics. In this study, we investigate the impacts of aerosol composition on tropospheric NO2 retrieval for an 18 year global data set from Global Ozone Monitoring Experiment (GOME)-series satellite sensors. With a focus on cloud-free scenes dominated by the presence of aerosols, individual aerosol composition affects the uncertainties of tropospheric NO2 columns through impacts on the aerosol loading amount, relative vertical distribution of aerosol and NO2, aerosol absorption properties, and surface albedo determination. Among aerosol compositions, secondary inorganic aerosol mostly dominates the NO2 uncertainty by up to 43.5% in urban agglomerations, while organic aerosols contribute significantly to the NO2 uncertainty by -8.9 to 37.3% during biomass burning seasons. The possible contrary influences from different aerosol species highlight the importance and complexity of aerosol correction on tropospheric NO2 retrieval and indicate the need for a full picture of aerosol properties. This is of particular importance for interpreting seasonal variations or long-term trends of tropospheric NO2 columns as well as for mitigating ozone and fine particulate matter pollution.

An injectable thermoresponsive-hydrogel for lamellar keratoplasty: In-situ releases celastrol and hampers corneal scars

Corneal stromal fibrosis is a common cause of visual impairment resulting from corneal injury, inflammation and surgery. Therefore, there is an unmet need for inhibiting corneal stromal fibrosis. However, bioavailability of topical eye drops is very low due to the tear and corneal barriers. In situ delivery offers a unique alternative to improve efficacy and minimize systemic toxicity. Herein, a drug delivery platform based on thermoresponsive injectable hydrogel/nano-micelles composite with in situ drug-controlled release and long-acting features is developed to prevent corneal scarring and reduce corneal stromal fibrosis in lamellar keratoplasty. The in-situ gelation hydrogels enabled direct delivery of celastrol to the corneal stroma. In vivo evaluation with a rabbit anterior lamellar keratoplasty model showed that hydrogel/micelles platform could effectively inhibit corneal stromal fibrosis. This strategy achieves controlled and prolonged release of celastrol in the corneal stroma of rabbit. Following a single corneal interlamellar injection, celastrol effectively alleviated fibrosis via mTORC1 signal promoting autophagy and inhibiting TGF-β1/Smad2/3 signaling pathway. Overall, this strategy demonstrates promise for the clinical application of celastrol in preventing corneal scarring and reducing corneal stromal fibrosis post-lamellar keratoplasty, highlighting the potential benefits of targeted drug delivery systems in ocular therapeutics.

Human Placenta Decellularized Extracellular Matrix Hydrogel Promotes the Generation of Human Spinal Cord Organoids with Dorsoventral Organization from Human Induced Pluripotent Stem Cells

Spinal cord organoids are of significant value in the research of spinal cord-related diseases by simulating disease states, thereby facilitating the development of novel therapies. However, the complexity of spinal cord structure and physiological functions, along with the lack of human-derived inducing components, presents challenges in the in vitro construction of human spinal cord organoids. Here, we introduce a novel human decellularized placenta-derived extracellular matrix hydrogel (DPECMH) and, combined with a new induction protocol, successfully construct human spinal cord organoids. The human placenta-sourced decellularized extracellular matrix (dECM), verified through hematoxylin and eosin staining, DNA quantification, and immunofluorescence staining, retained essential ECM components such as elastin, fibronectin, type I collagen, laminin, and so forth. The temperature-sensitive hydrogel made from human placenta dECM demonstrated good biocompatibility and promoted the differentiation of human induced pluripotent stem cell (hiPSCs)-derived spinal cord organoids into neurons. It displayed enhanced expression of laminar markers in comparison to Matrigel and showed higher expression of laminar markers compared to Matrigel, accelerating the maturation process of spinal cord organoids and demonstrating its potential as an organoid culture substrate. DPECMH has the potential to replace Matrigel as the standard additive for human spinal cord organoids, thus advancing the development of spinal cord organoid culture protocols and their application in the in vitro modeling of spinal cord-related diseases.

Structural determinants for membrane binding of the EGFR juxtamembrane domain

Overactivation of the epidermal growth factor receptor (EGFR) is critical for the development of multiple cancers. Previous studies have shown that the cell membrane is a key regulator of EGFR kinase activity through its interaction with the EGFR juxtamembrane domain (JM). However, the lipid recognition specificity of EGFR-JM and its interaction details remain unclear. Using lipid strip and liposome pulldown assays, we showed that EGFR-JM could specifically interact with PI(4,5)P2-or phosphatidylserine-containing membranes. We further characterized the JM-membrane interaction using NMR-titration-based chemical shift perturbation and paramagnetic relaxation enhancement analyses, and found that residues I649 - L659 comprised the membrane-binding site. Furthermore, the membrane-binding region contains the predicted dimerization motif of JM, 655LRRLL659, suggesting that membrane binding may affect JM dimerization and, therefore, regulate kinase activation.

Accessing Benzoazepine Derivatives via Photoinduced Radical Relay Formal [5 + 2] Reaction of Amide/Alkyne Enabled by Palladium Catalysis

A novel class of alkyne-tethered amides facilitates an unprecedented photoinduced palladium-catalyzed radical relay formal [5 + 2] reaction. This innovative strategy allows for the rapid construction of diverse fused benzoazepine structures, yielding structurally novel and compelling compounds. With a broad substrate scope and excellent functional group tolerance, the methodology synthesizes biologically active compounds. Notably, the resulting tricyclic benzo[b]azepines offer diversification opportunities through simple transformations. DFT calculations elucidate a seven-membered ring closure mechanism involving the alkenyl radical and Pd(I) rebound alongside a concerted metalation-deprotonation (CMD) process.

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations.

METHODS

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds.

FINDINGS

The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles.

INTERPRETATION

Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere.

FUNDING

Bill & Melinda Gates Foundation.

BadCM: Invisible Backdoor Attack Against Cross-Modal Learning

Despite remarkable successes in unimodal learning tasks, backdoor attacks against cross-modal learning are still underexplored due to the limited generalization and inferior stealthiness when involving multiple modalities. Notably, since works in this area mainly inherit ideas from unimodal visual attacks, they struggle with dealing with diverse cross-modal attack circumstances and manipulating imperceptible trigger samples, which hinders their practicability in real-world applications. In this paper, we introduce a novel bilateral backdoor to fill in the missing pieces of the puzzle in the cross-modal backdoor and propose a generalized invisible backdoor framework against cross-modal learning (BadCM). Specifically, a cross-modal mining scheme is developed to capture the modality-invariant components as target poisoning areas, where well-designed trigger patterns injected into these regions can be efficiently recognized by the victim models. This strategy is adapted to different image-text cross-modal models, making our framework available to various attack scenarios. Furthermore, for generating poisoned samples of high stealthiness, we conceive modality-specific generators for visual and linguistic modalities that facilitate hiding explicit trigger patterns in modality-invariant regions. To the best of our knowledge, BadCM is the first invisible backdoor method deliberately designed for diverse cross-modal attacks within one unified framework. Comprehensive experimental evaluations on two typical applications, i.e., cross-modal retrieval and VQA, demonstrate the effectiveness and generalization of our method under multiple kinds of attack scenarios. Moreover, we show that BadCM can robustly evade existing backdoor defenses. Our code is available at https://github.com/xandery-geek/BadCM.

Self-assembly of an amino acid derivative as an anode interface layer for advanced alkaline Al-air batteries

Alkaline Al-air batteries (AABs) are gaining increasing attention for large-scale energy storage systems due to their attractive intrinsic safety and cost-effectiveness. Nonetheless, the future development of AABs is substantially hampered by water-induced self-corrosion processes on the Al anode. In this work, we introduce an amino acid derivative, namely Nα-Boc-N1-formyl-L-tryptophan (NBLT), into a 4 M NaOH electrolyte to construct a unique layer that can effectively regulate the surface microstructure of the Al anode. The findings of the experiments show that NBLT can be used as a reliable corrosion inhibitor. The effectiveness of such inhibitors increases with NBLT concentration, reaching a maximum of 73.9% at 1.5 mM. In comparison to the pristine condition, there is a significant increase in anode utilization from 31.8% to 82.9%, capacity density from 947.9 to 2469.1 mA h g-1, and energy density from 1261.6 to 3384.6 W h kg-1. Theoretical calculations indicate that the carboxyl moieties present in the NBLT molecule establish coordination bonds with the Al atoms, thereby exerting a dominant role in the formation of the self-assembled barrier. The present investigation paves an effective strategy to inhibit reactions between anodes and electrolytes for advanced AABs.

Incorporating Network Pharmacology and Experimental Validation to Identify Bioactive Compounds and Potential Mechanisms of Digitalis in Treating Anaplastic Thyroid Cancer

Anaplastic thyroid cancer (ATC) is one of the most lethal malignant tumors for which there is no effective treatment. There are an increasing number of studies on herbal medicine for treating malignant tumors, and the classic botanical medicine Digitalis and its active ingredients for treating heart failure and arrhythmias have been revealed to have significant antitumor efficacy against a wide range of malignant tumors. However, the main components of Digitalis and the molecular mechanisms of its anti-ATC effects have not been extensively studied. Here, we screened the main components and core targets of Digitalis and verified the relationship between the active components and targets through network pharmacology, molecular docking, and experimental validation. These experiments showed that the active ingredients of Digitalis inhibit ATC cell activity and lead to ATC cell death through the apoptotic pathway.

MicroRNA-150-5P regulates Th1/Th2 cytokines expression levels by targeting EGR2 in allergic rhinitis

BACKGROUND

MiR-150-5p is one of the miRNAs in the expression profile of miRNAs, and in many previous studies, it has been shown that miR-150-5p may play an important role in peripheral blood dendritic cells (DCs) of allergic rhinitis (AR) patients. We sought to investigate the role and mechanism of miR-150-5p in regulating DC function by modulating EGR2 and influencing T cell derivation to promote AR development.

METHODS

The expression of miR-150-5p and EGR2 in AR patients was examined by real-time quantitative polymerase chain reaction (qRT-PCR), the expression of IL-4 cytokines in the supernatant of AR patients was tested by enzyme-linked immunosorbent assay (ELISA), and the expression of eosinophils in the supernatant of AR patients was measured by HE staining. The expression of EGR2 was detected by immunohistochemistry and fluorescent m-immunohistochemistry.

RESULTS

MiR-150-5p expression was up-regulated and EGR2 expression was down-regulated in peripheral blood DCs from AR patients. miR-150-5p upregulated DCs, which promoted T-cell differentiation. miR-150-5p further regulated EGR2, which suppressed DCs and caused alteration of T-cell differentiation, in turn triggering the occurrence of AR.

CONCLUSION

MiR-150-5p and its target gene EGR2 are involved in the development of AR, and DCs foster T-cell differentiation in peripheral blood of AR patients.

Decellularized Brain Extracellular Matrix Hydrogel Aids the Formation of Human Spinal-Cord Organoids Recapitulating the Complex Three-Dimensional Organization

The intricate electrophysiological functions and anatomical structures of spinal cord tissue render the establishment of in vitro models for spinal cord-related diseases highly challenging. Currently, both in vivo and in vitro models for spinal cord-related diseases are still underdeveloped, complicating the exploration and development of effective therapeutic drugs or strategies. Organoids cultured from human induced pluripotent stem cells (hiPSCs) hold promise as suitable in vitro models for spinal cord-related diseases. However, the cultivation of spinal cord organoids predominantly relies on Matrigel, a matrix derived from murine sarcoma tissue. Tissue-specific extracellular matrices are key drivers of complex organ development, thus underscoring the urgent need to research safer and more physiologically relevant organoid culture materials. Herein, we have prepared a rat decellularized brain extracellular matrix hydrogel (DBECMH), which supports the formation of hiPSC-derived spinal cord organoids. Compared with Matrigel, organoids cultured in DBECMH exhibited higher expression levels of markers from multiple compartments of the natural spinal cord, facilitating the development and maturation of spinal cord organoid tissues. Our study suggests that DBECMH holds potential to replace Matrigel as the standard culture medium for human spinal cord organoids, thereby advancing the development of spinal cord organoid culture protocols and their application in in vitro modeling of spinal cord-related diseases.

Single Layer Silk and Cotton Woven Fabrics for Acoustic Emission and Active Sound Suppression

Whether intentionally generating acoustic waves or attempting to mitigate unwanted noise, sound control is an area of challenge and opportunity. This study investigates traditional fabrics as emitters and suppressors of sound. When attached to a single strand of a piezoelectric fiber actuator, a silk fabric emits up to 70 dB of sound. Despite the complex fabric structure, vibrometer measurements reveal behavior reminiscent of a classical thin plate. Fabric pore size relative to the viscous boundary layer thickness is found-through comparative fabric analysis-to influence acoustic-emission efficiency. Sound suppression is demonstrated using two distinct mechanisms. In the first, direct acoustic interference is shown to reduce sound by up to 37 dB. The second relies on pacifying the fabric vibrations by the piezoelectric fiber, reducing the amplitude of vibration waves by 95% and attenuating the transmitted sound by up to 75%. Interestingly, this vibration-mediated suppression in principle reduces sound in an unlimited volume. It also allows the acoustic reflectivity of the fabric to be dynamically controlled, increasing by up to 68%. The sound emission and suppression efficiency of a 130 µm silk fabric presents opportunities for sound control in a variety of applications ranging from apparel to transportation to architecture.

Unsupervised Fusion Feature Matching for Data Bias in Uncertainty Active Learning

Active learning (AL) aims to sample the most valuable data for model improvement from the unlabeled pool. Traditional works, especially uncertainty-based methods, are prone to suffer from a data bias issue, which means that selected data cannot cover the entire unlabeled pool well. Although there have been lots of literature works focusing on this issue recently, they mainly benefit from the huge additional training costs and the artificially designed complex loss. The latter causes these methods to be redesigned when facing new models or tasks, which is very time-consuming and laborious. This article proposes a feature-matching-based uncertainty that resamples selected uncertainty data by feature matching, thus removing similar data to alleviate the data bias issue. To ensure that our proposed method does not introduce a lot of additional costs, we specially design a unsupervised fusion feature matching (UFFM), which does not require any training in our novel AL framework. Besides, we also redesign several classic uncertainty methods to be applied to more complex visual tasks. We conduct rigorous experiments on lots of standard benchmark datasets to validate our work. The experimental results show that our UFFM is better than the similar unsupervised feature matching technologies, and our proposed uncertainty calculation method outperforms random sampling, classic uncertainty approaches, and recent state-of-the-art (SOTA) uncertainty approaches.

Childhood emotional maltreatment and subsequent affective symptoms among chinese male drug users: The roles of impulsivity and psychological resilience

OBJECTIVE

Childhood emotional maltreatment (CEM) has been widely linked to later affective symptoms. What still remains inadequately understood are the potential nuanced differences in the consequences of childhood emotional abuse (CEM-A) versus childhood emotional neglect (CEM-N) and the implicated mechanisms. Research with non-Western, clinical samples also remains scarce. Thus, we examined the associations of CEM-A and CEM-N with later affective symptoms among Chinese male drug users and tested impulsivity and psychological resilience as potential mediators and moderators.

METHOD

Structural equation modeling analyses were conducted with survey data obtained from 239 Chinese male adult drug users who were in a rehabilitation center.

RESULTS

The mediating rather than the moderating hypotheses were supported. CEM-A was found to be positively associated with subsequent depressive and anxious symptoms through a positive association with impulsivity. In contrast, CEM-N was positively associated only with subsequent depressive symptoms via a negative association with psychological resilience. In addition, CEM-A was also found to be directly associated with later depressive and anxious symptoms.

CONCLUSIONS

CEM may pose a threat to later affective well-being partly through contributing to intrapersonal vulnerabilities as well as compromising intrapersonal strengths. Differentiating CEM-A and CEM-N appears to be critical for revealing the understudied specificity and nuance that may be inherently within such effects. Drug use treatment services should sensitively attend to the affective sequelae of CEM. Interventions targeted at the modification of impulsivity and the facilitation of psychological resilience may be effective in diminishing the affective consequences of CEM among drug users. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Water-Free Cyclosporine Ophthalmic Solution vs Vehicle for Dry Eye Disease: A Randomized Clinical Trial

Importance

Dry eye disease (DED) is a prevalent eye disorder. Cyclosporine is an effective immunomodulator that is widely used in DED; however, due to its highly hydrophobic nature, delivery of cyclosporine to the ocular surface is challenging.

Objective

To evaluate the efficacy and safety of SHR8028, a water-free cyclosporine ophthalmic solution, 0.1%, compared with vehicle in Chinese participants with DED.

Design, Setting, and Participants

This was a multicenter, double-blind, vehicle-controlled, phase 3 randomized clinical trial conducted from March 4, 2021, to July 22, 2022. Adult participants with moderate to severe DED were recruited from 12 hospitals in China. Study data were analyzed April 2, 2022, for the primary analysis.

Interventions

Following a 14-day run-in period with an artificial tear, participants were randomly assigned (1:1) to receive water-free cyclosporine or vehicle (1 eye drop in each eye twice daily). After a 29-day treatment, participants of both groups were given the option to receive water-free cyclosporine for an additional 12 weeks for longer-term safety assessment.

Main Outcomes and Measures

The primary end points were changes from baseline in total corneal fluorescein staining (tCFS) using the National Eye Institute scale and in dryness score on a visual analog scale at day 29.

Results

A total of 206 participants (mean [SD] age, 47.8 [14.2] years; 185 female [90%]) were enrolled, with 103 each in the cyclosporine group and the vehicle group. At day 29, the cyclosporine group experienced improved tCFS compared with vehicle (change [Δ] = -1.8; 95% CI, -2.7 to -1.0; P < .001), with a tCFS score decrease from baseline of -4.8 in the cyclosporine group and -3.0 in the vehicle group. Dryness score decreased from baseline in both groups (-19.2 vs -15.4; Δ = -3.8; 95% CI, -9.2 to 1.6; P = .17). During the 29-day treatment, treatment-related adverse events were reported in 15 participants (14.6%) in the cyclosporine group and 11 participants (10.7%) in the vehicle group.

Conclusions And Relevance

Results demonstrated superiority of a water-free cyclosporine, 0.1%, eye solution over vehicle in improving tCFS score at day 29 in Chinese participants with DED. However, dryness score (VAS) was not improved at day 29.

Trial Registration

ClinicalTrials.gov Identifier: NCT05841043.

Predictive value of crossover sign for outcome of ultrasound-guided vacuum aspiration in women with Cesarean scar pregnancy

OBJECTIVE

To examine the value of the crossover sign (COS) in predicting treatment outcome in women with a Cesarean scar pregnancy (CSP) who were treated with ultrasound-guided vacuum aspiration.

METHODS

This was a retrospective cohort study of women with CSP who underwent ultrasound-guided vacuum aspiration. Based on the relationship between the gestational sac, Cesarean scar and anterior wall of the uterus, CSPs were classified by COS type. Analysis was conducted to investigate the association between COS type (COS-1, COS-2) and treatment outcome. The incidence of treatment failure, retained pregnancy tissue, secondary therapy and bleeding ≥ 200 mL were analyzed.

RESULTS

In total, 181 eligible patients with CSP, including 90 (49.7%) women with COS-1 and 91 (50.3%) women with COS-2, were analyzed. COS-1 patients had a higher incidence of treatment failure compared with COS-2 patients (25.6% vs 8.8%; P = 0.003), as well as higher rates of retained pregnancy tissue (18.9% vs 6.6%; P = 0.013), secondary therapy (20.0% vs 6.6%; P = 0.002) and bleeding of ≥ 200 mL (13.3% vs 4.4%; P = 0.034). COS-1 and a large gestational sac (30.1-50.0 mm or >50.0 mm in diameter) were associated independently with increased risk of treatment failure (odds ratio, 4.57 (95% CI, 1.66-12.56); P = 0.003, 4.34 (95% CI, 1.35-13.94); P = 0.014 and 10.50 (95% CI, 2.54-43.46); P = 0.001, respectively).

CONCLUSIONS

Ultrasound evaluation of the relationship between the gestational sac and the endometrial line (COS classification) in women with CSP may help to predict treatment outcome among those undergoing vacuum aspiration. Among COS-1 patients, especially those with a gestational sac diameter of >30.0 mm, vacuum aspiration may be discouraged. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Varenicline solution nasal spray for dry eye disease in Chinese patients: a randomized phase 3 trial

Background

Dry eye disease has a high prevalence and exerts a significant negative effect on quality of life. In China, there are currently no available nasal sprays to promote natural tear production in patients with dry eye disease. We therefore evaluated the efficacy and safety of OC-01 (varenicline solution) nasal spray versus vehicle in Chinese patients with dry eye disease.

Methods

This was a randomized, multicenter, double-masked, vehicle-controlled, phase 3 clinical trial conducted at ophthalmology departments in 20 hospitals across China (NCT05378945). Eligible patients had a diagnosis of dry eye disease based on patient symptoms, Eye Dryness Score (EDS), Schirmer's Test (with topical anesthesia) Score (STS), and corneal fluorescein staining (CFS) score. Participants were randomly assigned 1:1 using an Interactive Web Response System (IWRS) to receive OC-01 0.6 mg/mL twice daily (BID) or vehicle nasal spray. Participants, investigators, and sponsor were all masked to treatment assignment. The primary endpoint was the percentage of subjects in the intention-to-treat population achieving ≥10 mm improvement in STS from baseline at week 4.

Findings

In total, 340 patients were randomized from 21 July 2022 to 04 April 2023, 78.8% were female. Patients in the OC-01 group (n = 176) had significantly higher achievement of ≥10 mm improvement in STS (35.8% [n = 63] versus 17.7% [n = 29], stratified odds ratio: 2.67, 95% CI: 1.570-4.533, p = 0.0002) and a significantly greater increase from baseline STS (least-squares mean difference [SE]: 3.87 [0.794], p < 0.0001) at week 4 versus the vehicle group (n = 164). In addition, OC-01 led to a numerically greater reduction in mean EDS from baseline at week 4 compared to the vehicle group (LS mean [SE] difference: -1.3 [2.20]; 95% CI: -5.64 to 2.99, p = 0.5467). The most common adverse event was mild, transient sneezing (78% of OC-01 administrations). No serious adverse events related to nasal administration occurred.

Interpretation

OC-01 (varenicline solution) nasal spray BID has clinically meaningful efficacy for reducing the signs (as measured by STS) and may improve the symptoms (as measured by EDS) of dry eye disease, with an excellent safety and tolerability profile, in the Chinese population.

Funding

Jixing Pharmaceutical Co. Ltd.

Hybrid Masked Image Modeling for 3D Medical Image Segmentation

Masked image modeling (MIM) with transformer backbones has recently been exploited as a powerful self-supervised pre-training technique. The existing MIM methods adopt the strategy to mask random patches of the image and reconstruct the missing pixels, which only considers semantic information at a lower level, and causes a long pre-training time. This paper presents HybridMIM, a novel hybrid self-supervised learning method based on masked image modeling for 3D medical image segmentation. Specifically, we design a two-level masking hierarchy to specify which and how patches in sub-volumes are masked, effectively providing the constraints of higher level semantic information. Then we learn the semantic information of medical images at three levels, including: 1) partial region prediction to reconstruct key contents of the 3D image, which largely reduces the pre-training time burden (pixel-level); 2) patch-masking perception to learn the spatial relationship between the patches in each sub-volume (region-level); and 3) drop-out-based contrastive learning between samples within a mini-batch, which further improves the generalization ability of the framework (sample-level). The proposed framework is versatile to support both CNN and transformer as encoder backbones, and also enables to pre-train decoders for image segmentation. We conduct comprehensive experiments on five widely-used public medical image segmentation datasets, including BraTS2020, BTCV, MSD Liver, MSD Spleen, and BraTS2023. The experimental results show the clear superiority of HybridMIM against competing supervised methods, masked pre-training approaches, and other self-supervised methods, in terms of quantitative metrics, speed performance and qualitative observations.

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

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

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

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

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Affiliation(s)

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

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Jasmonate signaling pathway confers salt tolerance through a NUCLEAR FACTOR-Y trimeric transcription factor complex in Arabidopsis

Jasmonate (JA) is a well-known phytohormone essential for plant response to biotic stress. Recently, a crucial role of JA signaling in salt resistance has been highlighted; however, the specific regulatory mechanism remains largely unknown. In this study, we found that the NUCLEAR FACTOR-Y (NF-Y) subunits NF-YA1, NF-YB2, and NF-YC9 form a trimeric complex that positively regulates the expression of salinity-responsive genes, whereas JASMONATE-ZIM DOMAIN protein 8 (JAZ8) directly interacts with three subunits and acts as the key repressor to suppress both the assembly of the NF-YA1-YB2-YC9 trimeric complex and the transcriptional activation activity of the complex. When plants encounter high salinity, JA levels are elevated and perceived by the CORONATINE INSENSITIVE (COI) 1 receptor, leading to the degradation of JAZ8 via the 26S proteasome pathway, thereby releasing the activity of the NF-YA1-YB2-YC9 complex, initiating the activation of salinity-responsive genes, such as MYB75, and thus enhancing the salinity tolerance of plants.

Temperature-Dependent Evaporative Anthropogenic VOC Emissions Significantly Exacerbate Regional Ozone Pollution

The evaporative emissions of anthropogenic volatile organic compounds (AVOCs) are sensitive to ambient temperature. This sensitivity forms an air pollution-meteorology connection that has not been assessed on a regional scale. We parametrized the temperature dependence of evaporative AVOC fluxes in a regional air quality model and evaluated the impacts on surface ozone in the Beijing-Tianjin-Hebei (BTH) area of China during the summer of 2017. The temperature dependency of AVOC emissions drove an enhanced simulated ozone-temperature sensitivity of 1.0 to 1.8 μg m-3 K-1, comparable to the simulated ozone-temperature sensitivity driven by the temperature dependency of biogenic VOC emissions (1.7 to 2.4 μg m-3 K-1). Ozone enhancements driven by temperature-induced AVOC increases were localized to their point of emission and were relatively more important in urban areas than in rural regions. The inclusion of the temperature-dependent AVOC emissions in our model improved the simulated ozone-temperature sensitivities on days of ozone exceedance. Our results demonstrated the importance of temperature-dependent AVOC emissions on surface ozone pollution and its heretofore unrepresented role in air pollution-meteorology interactions.

Enhanced burn wound healing by controlled-release 3D ADMSC-derived exosome-loaded hyaluronan hydrogel

Adipose mesenchymal stem cell (ADMSC)-derived exosomes (ADMSC-Exos) have shown great potential in regenerative medicine and been evidenced benefiting wound repair such as burns. However, the low yield, easy loss after direct coating, and no suitable loading system to improve their availability and efficacy hinder their clinical application for wound healing. And few studies focused on the comparison of biological functions between exosomes derived from different culture techniques, especially in exosome-releasing hydrogel system. Therefore, we designed a high-performance exosome controllable releasing hydrogel system for burn wound healing, namely loading 3D-printed microfiber culture-derived exosomes in a highly biocompatible hyaluronic acid (HA). In this project, we compared the biological functions in vitro and in a burn model among exosomes derived from the conventional two-dimensional (2D) plate culture (2D-Exos), microcarrier culture (2.5D-Exos), and 3D-printed microfiber culture (3D-Exos). Results showed that compared with 2D-Exos and 2.5D-Exos, 3D-Exos promoted HACATs and HUVECs cell proliferation and migration more significantly. Additionally, 3D-Exos had stronger angiogenesis-promoting effects in tube formation of (HUVECs) cells. Moreover, we found HA-loaded 3D-Exos showed better burn wound healing promotion compared to 2D-Exos and 2.5D-Exos, including accelerated burn wound healing rate and better collagen remodeling. The study findings reveal that the HA-loaded, controllable-release 3D-Exos repair system distinctly augments therapeutic efficacy in terms of wound healing, while concurrently introducing a facile application approach. This system markedly bolsters the exosomal loading efficiency, provides a robust protective milieu, and potentiates the inherent biological functionalities of the exosomes. Our findings provide a rationale for more efficient utilization of high-quality and high-yield 3D exosomes in the future, and a novel strategy for healing severe burns.

The adaptor protein ECAP, the co-repressor LEUNIG, and the transcription factor BEH3 interact and regulate microsporocyte generation in Arabidopsis

Histo-specification and morphogenesis of anthers during development in Arabidopsis (Arabidopsis thaliana) are well understood. However, the regulatory mechanism of microsporocyte generation at the pre-meiotic stage remains unclear, especially how archesporial cells are specified and differentiate into two cell lineages with distinct developmental fates. SPOROCYTELESS (SPL) is a key reproductive gene that is activated during early anther development and remains active. In this study, we demonstrated that the EAR motif-containing adaptor protein (ECAP) interacts with the Gro/Tup1 family co-repressor LEUNIG (LUG) and the BES1/BZR1 HOMOLOG3 (BEH3) transcription factor to form a transcription activator complex, epigenetically regulating SPL transcription. SPL participates in microsporocyte generation by modulating the specification of archesporial cells and the archesporial cell-derived differentiation of somatic and reproductive cell layers. This study illustrates the regulation of SPL expression by the ECAP-LUG-BEH3 complex, which is essential for the generation of microsporocytes. Moreover, our findings identified ECAP as a key transcription regulator that can combine with different partners to regulate gene expression in distinct ways, thereby facilitating diverse processes in various aspects of plant development.

Fatostatin promotes anti-tumor immunity by reducing SREBP2 mediated cholesterol metabolism in tumor-infiltrating T lymphocytes

Aberrant lipid metabolism impacts intratumoral T cell-mediated immune response and tumor growth. Fatostatin functions as an inhibitor of sterol regulatory element binding protein (SREBP) activation. However, the complex effects of fatostatin on cholesterol metabolism in the tumor microenvironment (TME) and its influence on T cell anti-tumor immunity remain unclear. In this study, fatostatin effectively suppressed B16 melanoma, MC38 colon cancer, and Lewis lung cancer (LLC) transplanted tumor growth in immunocompetent mice by reducing SREBPs-mediated lipid metabolism, especially cholesterol levels. Mechanistically, fatostatin decreased intracellular cholesterol accumulation and inhibited X-box binding protein 1 (XBP1)-mediated endoplasmic reticulum (ER) stress, reducing Treg cells and alleviating CD8+ T cell exhaustion in the TME, exerting anti-tumor activity. Nevertheless， this effect was impaired in immunodeficient nude mice, suggesting fatostatin's anti-tumor efficacy in transplanted tumors partly relies on T cell-mediated anti-tumor immunity. Our study highlights SREBP2-mediated cholesterol metabolism as a potential strategy for anti-tumor immunotherapy, and confirms fatostatin's promise in tumor immunotherapy.

Emodin Blocks mPTP Opening and Improves LPS-Induced HMEC-1 Cell Injury by Upregulation of ATP5A1

BACKGROUND

Emodin has been shown to exert anti-inflammatory and cytoprotective effects. Our study aimed to identify a novel anti-inflammatory mechanism of emodin.

METHODS

An LPS-induced model of microvascular endothelial cell (HMEC-1) injury was constructed. Cell proliferation was examined using a CCK-8 assay. The effects of emodin on reactive oxygen species (ROS), cell migration, the mitochondrial membrane potential (MMP), and the opening of the mitochondrial permeability transition pore (mPTP) were evaluated. Actin-Tracker Green was used to examine the relationship between cell microfilament reconstruction and ATP5A1 expression. The effects of emodin on the expression of ATP5A1, NALP3, and TNF-α were determined. After treatment with emodin, ATP5A1 and inflammatory factors (TNF-α, IL-1, IL-6, IL-13 and IL-18) were examined by Western blotting.

RESULTS

Emodin significantly increased HMEC-1 cell proliferation and migration, inhibited the production of ROS, increased the mitochondrial membrane potential, and blocked the opening of the mPTP. Moreover, emodin could increase ATP5A1 expression, ameliorate cell microfilament remodeling, and decrease the expression of inflammatory factors. In addition, when ATP5A1 was overexpressed, the regulatory effect of emodin on inflammatory factors was not significant.

CONCLUSION

Our findings suggest that emodin can protect HMEC-1 cells against inflammatory injury. This process is modulated by the expression of ATP5A1.

[Prognostic nutritional index application value for acute-on-chronic liver failure co-infection]

Objective: To explore the predictive value of the prognostic nutritional index (PNI) in concurrently infected patients with acute-on-chronic liver failure (ACLF). Methods: 220 cases with ACLF diagnosed and treated at the First Affiliated Hospital of Xi'an Jiaotong University from January 2011 to December 2016 were selected. Patients were divided into an infection and non-infection group according to whether they had co-infections during the course of the disease. Clinical data differences were compared between the two groups of patients. Binary logistic regression analysis was used to screen out influencing factors related to co-infection. The receiver operating characteristic curve was used to evaluate the predictive value of PNI for ACLF co-infection. The measurement data between groups were compared using the independent sample t-test and the Mann-Whitney U rank sum test. The enumeration data were analyzed using the Fisher exact probability test or the Pearson χ(2) test. The Pearson method was performed for correlation analysis. The independent risk factors for liver failure associated with co-infection were analyzed by multivariate logistic analysis. Results: There were statistically significant differences in ascites, hepatorenal syndrome, PNI score, and albumin between the infection and the non-infection group (P < 0.05). Among the 220 ACLF cases, 158 (71.82%) were infected with the hepatitis B virus (HBV). The incidence rate of infection during hospitalization was 69.09% (152/220). The common sites of infection were intraabdominal (57.07%) and pulmonary infection (29.29%). Pearson correlation analysis showed that PNI and MELD-Na were negatively correlated (r = -0.150, P < 0.05). Multivariate logistic analysis results showed that low PNI score (OR=0.916, 95%CI: 0.865~0.970), ascites (OR=4.243, 95%CI: 2.237~8.047), and hepatorenal syndrome (OR=4.082, 95%CI : 1.106~15.067) were risk factors for ACLF co-infection (P < 0.05). The ROC results showed that the PNI curve area (0.648) was higher than the MELD-Na score curve area (0.610, P < 0.05). The effectiveness of predicting infection risk when PNI was combined with ascites and hepatorenal syndrome complications was raised. Patients with co-infections had a good predictive effect when PNI ≤ 40.625. The sensitivity and specificity were 84.2% and 41.2%, respectively. Conclusion: Low PNI score and ACLF co-infection have a close correlation. Therefore, PNI has a certain appraisal value for ACLF co-infection.

GLABRA 2 regulates ETHYLENE OVERPRODUCER 1 accumulation during nutrient deficiency-induced root hair growth

Root hairs (RHs), extensive structures of root epidermal cells, are important for plant nutrient acquisition, soil anchorage, and environmental interactions. Excessive production of the phytohormone ethylene (ET) leads to substantial root hair growth, manifested as tolerance to plant nutrient deficiencies. However, the molecular basis of ET production during root hair growth in response to nutrient starvation remains unknown. Herein, we found that a critical transcription factor, GLABRA 2 (GL2), inhibits ET production during root hair growth in Arabidopsis (Arabidopsis thaliana). GL2 directly binds to the promoter of the gene encoding ET OVERPRODUCER 1 (ETO1), one of the most important ET-production-regulation factors, in vitro and in vivo, and then regulates the accumulation and function of ETO1 in root hair growth. The GL2-regulated-ETO1 module is required for promoting root hair growth under nitrogen, phosphorus, or potassium deficiency. Genome-wide analysis revealed numerous genes, such as ROOT HAIR DEFECTIVE 6-LIKE 4, ETHYLENE-INSENSITIVE 3-LIKE 2, ROOT HAIR SPECIFIC 13, are involved in the GL2-regulated-ETO1 module. Our work reveals a key transcription mechanism in the control of ET production during root hair growth under three major nutrient deficiencies.

RNA editing enzymes: structure, biological functions and applications

With the advancement of sequencing technologies and bioinformatics, over than 170 different RNA modifications have been identified. However, only a few of these modifications can lead to base pair changes, which are called RNA editing. RNA editing is a ubiquitous modification in mammalian transcriptomes and is an important co/posttranscriptional modification that plays a crucial role in various cellular processes. There are two main types of RNA editing events: adenosine to inosine (A-to-I) editing, catalyzed by ADARs on double-stranded RNA or ADATs on tRNA, and cytosine to uridine (C-to-U) editing catalyzed by APOBECs. This article provides an overview of the structure, function, and applications of RNA editing enzymes. We discuss the structural characteristics of three RNA editing enzyme families and their catalytic mechanisms in RNA editing. We also explain the biological role of RNA editing, particularly in innate immunity, cancer biogenesis, and antiviral activity. Additionally, this article describes RNA editing tools for manipulating RNA to correct disease-causing mutations, as well as the potential applications of RNA editing enzymes in the field of biotechnology and therapy.

Clinical report of microsurgical treatment of Kohler's disease

The conservative treatment for Kohler's disease will take several months, but some patients still have flatfoot and persistent pain. From October 2013 to July 2015, 3 children with Kohler's disease underwent navicular decompression and micro-circulation reconstruction surgery in our hospital. All the patients have received conservative treatment for more than 3 months and the effect was poor. X-ray showed the bone density of navicular increased significantly. All patients were followed up over 1 year. The 3 patients recovered well. VAS score decreased from 7.0 to 2.6 at 1 month after the operation. The pain symptom disappeared completely on 3 months after surgery. The density of navicular bone recovered to normal. Navicular decompression and micro-circulation reconstruction surgery may quickly improve the ischemic status of navicular bone, alleviate pain symptom and enable patients to resume normal activity as soon as possible.

Tunneling Interpenetrative Lithium Ion Conduction Channels in Polymer-in-Ceramic Composite Solid Electrolytes

Polymer-in-ceramic composite solid electrolytes (PIC-CSEs) provide important advantages over individual organic or inorganic solid electrolytes. In conventional PIC-CSEs, the ion conduction pathway is primarily confined to the ceramics, while the faster routes associated with the ceramic-polymer interface remain blocked. This challenge is associated with two key factors: (i) the difficulty in establishing extensive and uninterrupted ceramic-polymer interfaces due to ceramic aggregation; (ii) the ceramic-polymer interfaces are unresponsive to conducting ions because of their inherent incompatibility. Here, we propose a strategy by introducing polymer-compatible ionic liquids (PCILs) to mediate between ceramics and the polymer matrix. This mediation involves the polar groups of PCILs interacting with Li+ ions on the ceramic surfaces as well as the interactions between the polar components of PCILs and the polymer chains. This strategy addresses the ceramic aggregation issue, resulting in uniform PIC-CSEs. Simultaneously, it activates the ceramic-polymer interfaces by establishing interpenetrating channels that promote the efficient transport of Li+ ions across the ceramic phase, the ceramic-polymer interfaces, and the intervening pathways. Consequently, the obtained PIC-CSEs exhibit high ionic conductivity, exceptional flexibility, and robust mechanical strength. A PIC-CSE comprising poly(vinylidene fluoride) (PVDF) and 60 wt % PCIL-coated Li3Zr2Si2PO12 (LZSP) fillers showcasing an ionic conductivity of 0.83 mS cm-1, a superior Li+ ion transference number of 0.81, and an elongation of ∼300% at 25 °C could be produced on meter-scale. Its lithium metal pouch cells show high energy densities of 424.9 Wh kg-1 (excluding packing films) and puncture safety. This work paves the way for designing PIC-CSEs with commercial viability.

Risk stratification by systemic manifestations secondary to hemodynamic disorders of patients with severe tricuspid regurgitation

BACKGROUND

Tricuspid regurgitation (TR) is a prevalent disease that triggers systemic pathological changes including cardiac, respiratory, hepatic and digestive, hematopoietic, renal and skin issues. The burden of extra-cardiac manifestations has not been well described in TR patients and the clinical impact is unknown.

METHODS

Patients with severe or more-than-severe TR during hospitalization, who did not have any previous cardiac procedures, hemodynamically significant congenital heart disease or concomitant severe aortic or mitral valve disease, were retrospectively analyzed. Pre-specified criteria and diagnosis of baseline characteristics were used to evaluate the presence of extra-cardiac manifestations secondary to TR after excluding comorbidities that may also lead to corresponding abnormalities. Extra-cardiac involvements encompass respiratory, hepatic and, digestive, renal, hematopoietic and dermatic system. Staging criteria are defined as no extra-cardiac system involvement in Stage 1, one in Stage 2, at least two extra-cardiac involvements in Stage 3 and any end-stage organ failure in Stage 4. A telephone follow-up was conducted to record the composite endpoint namely all-cause death or cardiac rehospitalization after the index hospitalization.

RESULTS

A total of 258 patients were identified with a median age of 73 (interquartile range [IQR]: 62-83) years and 52.3% were female. Severe TR and more-than-severe TR patients accounted for 92.6% and 7.4% of the cohort. There were 20.5%, 27.5%, 37.6% and 14.3% of patients from Stage 1 to 4 respectively. The follow-up time was at a median of 251 (IQR: 183-324) days. TR Patients in Stage 3&4 were at an increased risk with borderline statistical significance to experience the composite endpoint compared to patients in Stage 1&2 (odds ratio [OR] 1.9, 95% confidence interval [CI] 1.0 to 3.7, P = 0.049).

CONCLUSIONS

Approximately half of patients with at least severe TR presented with two or more extra-cardiac systemic manifestations, which may incur a 1.9-fold higher risk of all-cause death or cardiac rehospitalization than TR patients with one or less extra-cardiac involvement.

Deciphering the Enhancing Impact of Exogenous Brassinolide on Physiological Indices of Melon Plants under Downy Mildew-Induced Stress

Melon (Cucumis melo L.) is a valuable horticultural crop of the Cucurbitaceae family. Downy mildew (DM), caused by Pseudoperonospora cubensis, is a significant inhibitor of the production and quality of melon. Brassinolide (BR) is a new type of phytohormone widely used in cultivation for its broad spectrum of resistance- and defense-mechanism-improving activity. In this study, we applied various exogenous treatments (0.5, 1.0, and 2.0 mg·L-1) of BR at four distinct time periods (6 h, 12 h, 24 h, and 48 h) and explored the impact of BR on physiological indices and the genetic regulation of melon seedling leaves infected by downy-mildew-induced stress. It was mainly observed that a 2.0 mg·L-1 BR concentration effectively promoted the enhanced photosynthetic activity of seedling leaves, and quantitative real-time polymerase chain reaction (qRT-PCR) analysis similarly exhibited an upregulated expression of the predicted regulatory genes of photosystem II (PSII) CmHCF136 (MELO3C023596.2) and CmPsbY (MELO3C010708.2), thus indicating the stability of the PSII reaction center. Furthermore, 2.0 mg·L-1 BR resulted in more photosynthetic pigments (nearly three times more than the chlorophyll contents (264.52%)) as compared to the control and other treatment groups and similarly upregulated the expression trend of the predicted key enzyme genes CmLHCP (MELO3C004214.2) and CmCHLP (MELO3C017176.2) involved in chlorophyll biosynthesis. Meanwhile, the maximum contents of soluble sugars and starch (186.95% and 164.28%) were also maintained, which were similarly triggered by the upregulated expression of the predicted genes CmGlgC (MELO3C006552.2), CmSPS (MELO3C020357.2), and CmPEPC (MELO3C018724.2), thereby maintaining osmotic adjustment and efficiency in eliminating reactive oxygen species. Overall, the exogenous 2.0 mg·L-1 BR exhibited maintained antioxidant activities, plastid membranal stability, and malondialdehyde (MDA) content. The chlorophyll fluorescence parameter values of F0 (42.23%) and Fv/Fm (36.67%) were also noticed to be higher; however, nearly three times higher levels of NPQ (375.86%) and Y (NPQ) (287.10%) were observed at 48 h of treatment as compared to all other group treatments. Increased Rubisco activity was also observed (62.89%), which suggested a significant role for elevated carbon fixation and assimilation and the upregulated expression of regulatory genes linked with Rubisco activity and the PSII reaction process. In short, we deduced that the 2.0 mg·L-1 BR application has an enhancing effect on the genetic modulation of physiological indices of melon plants against downy mildew disease stress.

Investigation of the ΔI=1/2 Rule and Test of CP Symmetry through the Measurement of Decay Asymmetry Parameters in Ξ^{-} Decays

Using (10087±44)×10^{6}  J/ψ events collected with the BESIII detector, numerous Ξ^{-} and Λ decay asymmetry parameters are simultaneously determined from the process J/ψ→Ξ^{-}Ξ[over ¯]^{+}→Λ(pπ^{-})π^{-}Λ[over ¯](n[over ¯]π^{0})π^{+} and its charge-conjugate channel. The precisions of α_{Λ0} for Λ→nπ^{0} and α[over ¯]_{Λ0} for Λ[over ¯]→n[over ¯]π^{0} compared to world averages are improved by factors of 4 and 1.7, respectively. The ratio of decay asymmetry parameters of Λ→nπ^{0} to that of Λ→pπ^{-}, ⟨α_{Λ0}⟩/⟨α_{Λ-}⟩, is determined to be 0.873±0.012_{-0.010}^{+0.011}, where the first and the second uncertainties are statistical and systematic, respectively. The ratio is smaller than unity more than 5σ, which signifies the existence of the ΔI=3/2 transition in Λ for the first time. Besides, we test for CP symmetry in Ξ^{-}→Λπ^{-} and in Λ→nπ^{0} with the best precision to date.

Prevalence of metabolic syndrome in patients with inflammatory bowel disease: a systematic review and meta-analysis

OBJECTIVES

Patients with inflammatory bowel disease (IBD) may experience comorbidities involving metabolic syndrome (MetS). However, this association remains controversial. Our objective was to estimate the prevalence of MetS in patients with IBD and assess whether MetS is more strongly associated with ulcerative colitis (UC) or Crohn's disease (CD).

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

PubMed, Cochrane Library, Web of Science, EMBASE and MEDLINE were searched from their inception to July 2022.

ELIGIBILITY CRITERIA

Observational studies reporting data regarding the rate of comorbid MetS among patients with IBD and published in English.

DATA EXTRACTION AND SYNTHESIS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses and the Meta-analysis of Observational Studies in Epidemiology reporting guidelines were followed. Pooled prevalence, ORs and 95% CIs were calculated using random-effects models. The Newcastle-Ottawa Scale and the Agency for Healthcare Research and Quality checklist were used. Heterogeneity, sensitivity and stratified analyses were performed using R (V.4.2.1).

RESULTS

11 eligible studies involving 2501 patients were included. Of these studies, four reported MetS prevalence separately by IBD phenotype, and only one contained a non-IBD comparison group. Overall, the methodological quality of the included studies was moderate. The pooled prevalence of MetS in IBD was 19.4% (95% CI 15.1% to 23.8%), with a moderate heterogeneity (I2=51.8%, Cochrane Q statistic=12.4, p=0.053). Stratified analyses demonstrated that the aggregate estimate of comorbid MetS was significantly higher in UC than in CD (38.2% vs 13.6%, χ2=4.88, p=0.03). We found a positive association between MetS and UC compared with CD (OR=2.11, 95% CI 1.19 to 3.74, p=0.01). Additionally, four studies identified that higher age was a risk factor associated with the development of MetS.

CONCLUSIONS

MetS is not rare in IBD, especially in UC. However, longitudinal studies are needed to further clarify the relationship between IBD and MetS.

PROSPERO REGISTRATION NUMBER

CRD42022346340.

Pd(0)-Catalyzed Asymmetric Cyclization/Coupling Cascade of Alkyne-Tethered Unsaturated Carbonyls: Development and Mechanism Elucidation

While the Pd(0)-catalyzed cyclization of alkyne-tethered unsaturated carbonyl substrates has been reported, the mechanism has not been well elucidated, and the potential asymmetric version remains to be developed. Here, we disclose that a chiral Pd(0) complex can efficiently promote the desymmetrizative cyclization of alkyne-tethered cyclohexadienones in CH3OH, and the resultant Pd(II) intermediates further undergo an array of tandem coupling reactions, including Suzuki, Sonogashira, and even chemoselective reduction by CH3OH in the absence of additional coupling partners. As a result, a broad spectrum of hydrobenzofuran derivatives, having a tetra- or trisubstituted exo-alkene motif, is constructed with moderate to outstanding enantioselectivity in an exclusive cis-difunctionalization pattern. In addition, this enantioselective protocol can be well expanded to linear alkyne-tethered unsaturated carbonyls, and a new desymmetrizative and asymmetric cyclization/coupling cascade of bis-alkyne-tethered enones is further realized efficiently, furnishing diversely structured frameworks with high stereoselectivity. Moreover, kinetic transformation for various racemic alkyne-tethered enones can be accomplished under similar catalytic conditions, and unusual kinetic reactions by chemoselectively undertaking Suzuki or Sonogashira coupling, or reduction by CH3OH, occur sequentially, finally yielding two types of chiral products, both with high enantioselectivity via either ligand- or substrate-based control. The experimental results demonstrate that the current Pd(0)-based strategy is superior to the classical Pd(II)-catalyzed carbopalladation/cyclization process of the identical substrates with regard to enantioselectivity and synthetic versatility. Moreover, density functional theory calculations are conducted to rationalize the Pd(0)-catalyzed oxidative cyclometalation pathway in the key cyclization step, which leads to the observed cis-difunctionalized products exclusively.

Independent associations of serum calcium with or without albumin adjustment and serum phosphorus with nonalcoholic fatty liver disease: results from NHANES 1999-2018

Background

The associations of serum calcium and phosphorus with nonalcoholic fatty liver disease (NAFLD) remain unclear. In addition, there may be an effect of albumin correction on the association between serum calcium and NAFLD. We aimed to explore these relationships in the National Health and Nutrition Examination Survey (NHANES).

Methods

Eligible adult individuals from NHANES 1999-2018 were recruited for the study. We explored the associations of serum calcium, albumin-adjusted serum calcium, and serum phosphorus with NAFLD in multivariable-adjusted regression models. In addition, restricted cubic spline (RCS), stratified analysis, and multiple sensitivity analyses were used for further elaboration.

Results

The study sample consisted of 20,900 participants, with an observed NAFLD prevalence of 44.65%. Fully adjusted models indicated that serum calcium was inversely associated with NAFLD (odds ratio [OR] and 95% confidence interval [CI] = 0.70 (0.62, 0.78), p<0.0001), whereas albumin-adjusted serum calcium was positively associated with NAFLD (OR and 95% CI=1.59 (1.41, 1.79), p<0.0001). RCS modeling indicated that serum calcium without and with albumin adjustment was linearly(p nonlinear = 0.083) and nonlinearly (p nonlinear < 0.0001) associated with NAFLD, respectively, whereas serum phosphorus showed a U-shaped relationship with NAFLD(p nonlinear < 0.0001). Gender is a significant influence in all associations, and other variables may also have an effect. Sensitivity analyses indicated that these associations were independent of additional significant confounders.

Conclusion

Serum calcium and phosphorus were significantly associated with the development of NAFLD. These findings suggest the potential clinical significance of serum calcium/phosphorus and albumin levels in individuals at high risk for NAFLD. Our study supports the potential role of serum calcium/phosphorus homeostasis in the pathophysiology of NAFLD and could serve as NAFLD-related biomarkers.