Interplay between the glymphatic system and neurotoxic proteins in Parkinson's disease and related disorders: current knowledge and future directions

Parkinson's disease is a common neurodegenerative disorder that is associated with abnormal aggregation and accumulation of neurotoxic proteins, including α-synuclein, amyloid-β, and tau, in addition to the impaired elimination of these neurotoxic protein. Atypical parkinsonism, which has the same clinical presentation and neuropathology as Parkinson's disease, expands the disease landscape within the continuum of Parkinson's disease and related disorders. The glymphatic system is a waste clearance system in the brain, which is responsible for eliminating the neurotoxic proteins from the interstitial fluid. Impairment of the glymphatic system has been proposed as a significant contributor to the development and progression of neurodegenerative disease, as it exacerbates the aggregation of neurotoxic proteins and deteriorates neuronal damage. Therefore, impairment of the glymphatic system could be considered as the final common pathway to neurodegeneration. Previous evidence has provided initial insights into the potential effect of the impaired glymphatic system on Parkinson's disease and related disorders; however, many unanswered questions remain. This review aims to provide a comprehensive summary of the growing literature on the glymphatic system in Parkinson's disease and related disorders. The focus of this review is on identifying the manifestations and mechanisms of interplay between the glymphatic system and neurotoxic proteins, including loss of polarization of aquaporin-4 in astrocytic endfeet, sleep and circadian rhythms, neuroinflammation, astrogliosis, and gliosis. This review further delves into the underlying pathophysiology of the glymphatic system in Parkinson's disease and related disorders, and the potential implications of targeting the glymphatic system as a novel and promising therapeutic strategy.

Enhanced hepatic metabolic perturbation of polystyrene nanoplastics by UV irradiation-induced hydroxyl radical generation

The environmental behavior of and risks associated with nanoplastics (NPs) have attracted considerable attention. However, compared to pristine NPs, environmental factors such as ultraviolet (UV) irradiation that lead to changes in the toxicity of NPs have rarely been studied. We evaluated the changes in morphology and physicochemical properties of polystyrene (PS) NPs before and after UV irradiation, and compared their hepatotoxicity in mice. The results showed that UV irradiation caused particle size reduction and increased the carbonyl index (CI) and negative charge on the particle surface. UV-aged PS NPs (aPS NPs) could induce the generation of hydroxyl radicals (·OH), but also further promoted the generation of ·OH in the Fenton reaction system. Hepatic pathological damage was more severe in mice exposed to aPS NPs, accompanied by a large number of vacuoles and hepatocyte balloon-like changes and more marked perturbations in blood glucose and serum lipoprotein, alanine aminotransferase and aspartate aminotransferase levels. In addition, exposure to PS NPs and aPS NPs, especially aPS NPs, triggered oxidative stress and significantly damaged the antioxidant capacity of mice liver. Compared with PS NPs, exposure to aPS NPs increased the number of altered metabolites in hepatic and corresponding metabolic pathways, especially glutathione metabolism. Our research suggests that UV irradiation can disrupt the redox balance in organisms by promoting the production of ·OH, enhancing PS NPs-induced liver damage and metabolic disorders. This study will help us understand the health risks of NPs and to avoid underestimation of the risks of NPs in nature.

Optimal channel dynamic selection for Constructing lightweight Data EEG-based emotion recognition

At present, most methods to improve the accuracy of emotion recognition based on electroencephalogram (EEG) are achieved by means of increasing the number of channels and feature types. This is to use the big data to train the classification model but it also increases the code complexity and consumes a large amount of computer time. We propose a method of Ant Colony Optimization with Convolutional Neural Networks and Long Short-Term Memory (ACO-CNN-LSTM) which can attain the dynamic optimal channels for lightweight data. First, transform the time-domain EEG signal to the frequency domain by Fast Fourier Transform (FFT), and the Differential Entropy (DE) of the three frequency bands (α , β and γ ) are extracted as the feature data; Then, based on the DE feature dataset, ACO is employed to plan the path where the electrodes are located in the brain map. The classification accuracy of CNN-LSTM is used as the objective function for path determination, and the electrodes on the optimal path are used as the optimal channels; Next, the initial learning rate and batchsize parameters are exactly matched the data characteristics, which can obtain the best initial learning rate and batchsize; Finally, the SJTU Emotion EEG Dataset (SEED) dataset is used for emotion recognition based on the ACO-CNN-LSTM. From the experimental results, it can be seen that: the average accuracy of three-classification (positive, neutral, negative) can achieve 96.59 %, which is based on the lightweight data by means of ACO-CNN-LSTM proposed in the paper. Meanwhile, the computer time consumed is reduced. The computational efficiency is increased by 15.85 % compared with the traditional CNN-LSTM method. The accuracy can achieve more than 90 % when the data volume is reduced to 50 %. In summary, the proposed method of ACO-CNN-LSTM in the paper can get higher efficiency and accuracy.

Nanoscale Local Contacts Enable Inverted Inorganic Perovskite Solar Cells with 20.8 % Efficiency

Inorganic perovskite solar cells (IPSCs) have gained significant attention due to their excellent thermal stability and suitable band gap (~1.7 eV) for tandem solar cell applications. However, the defect-induced non-radiative recombination losses, low charge extraction efficiency, energy level mismatches, and so on render the fabrication of high-efficiency inverted IPSCs remains challenging. Here, the use of 3-amino-5-bromopyridine-2-formamide (ABF) in methanol was dynamically spin-coated on the surface of CsPbI2.85Br0.15 film, which facilitates the limited etching of defect-rich subsurface layer, resulting in the formation of vertical PbI2 nanosheet structures. This enabled localized contacts between the perovskite film and the electron transport layer, suppress the recombination of electron-hole and beneficial to electron extraction. Additionally, the C=O and C=N groups in ABF effectively passivated the undercoordinated Pb2+ at grain boundaries and on the surface of CsPbI2.85Br0.15 film. Eventually, we achieved a champion efficiency of 20.80 % (certified efficiency of 20.02 %) for inverted IPSCs with enhanced stability, which is the highest value ever reported to date. Furthermore, we successfully prepared p-i-n type monolithic inorganic perovskite/silicon tandem solar cells (IPSTSCs) with an efficiency of 26.26 %. This strategy provided both fast extraction and efficient passivation at the electron-selective interface.

Textured Perovskite/Silicon Tandem Solar Cells Achieving Over 30% Efficiency Promoted by 4-Fluorobenzylamine Hydroiodide

Monolithic textured perovskite/silicon tandem solar cells (TSCs) are expected to achieve maximum light capture at the lowest cost, potentially exhibiting the best power conversion efficiency. However, it is challenging to fabricate high-quality perovskite films and preferred crystal orientation on commercially textured silicon substrates with micrometer-size pyramids. Here, we introduced a bulky organic molecule (4-fluorobenzylamine hydroiodide (F-PMAI)) as a perovskite additive. It is found that F-PMAI can retard the crystallization process of perovskite film through hydrogen bond interaction between F- and FA+ and reduce (111) facet surface energy due to enhanced adsorption energy of F-PMAI on the (111) facet. Besides, the bulky molecular is extruded to the bottom and top of perovskite film after crystal growth, which can passivate interface defects through strong interaction between F-PMA+ and undercoordinated Pb2+/I-. As a result, the additive facilitates the formation of large perovskite grains and (111) preferred orientation with a reduced trap-state density, thereby promoting charge carrier transportation, and enhancing device performance and stability. The perovskite/silicon TSCs achieved a champion efficiency of 30.05% based on a silicon thin film tunneling junction. In addition, the devices exhibit excellent long-term thermal and light stability without encapsulation. This work provides an effective strategy for achieving efficient and stable TSCs.

Changes in cargoes of platelet derived extracellular vesicles heterogeneous subpopulations induced by PM0.1--Undisclosed cardiovascular injury communication mechanism

Epidemiological evidence has indicated a closely link between PM0.1 exposure and the incidence rate of cardiovascular diseases. This study explores the underlying communication roles of platelet-derived extracellular vesicles (PEVs) heterogeneous subpopulations in cardiovascular injury. PEVs and PMEVs which were extracted from platelet-rich plasma (PRP) un-exposure or exposure to PM0.1 by TIM4 affinity beads. By optimizing separation conditions, replacing pipelines, and resetting injection procedures, Asymmetric flow field-flow fractionation (AF4) was employed to separate, purify, characterize, and enrich PEVs and PMEVs heterogeneous subpopulations (small PEVs, PEVs-S/PMEVs-S: <100 nm; medium PEVs, PEVs-M/PMEVs-M: 100-200 nm; and large PEVs, PEVs-L/PMEVs-L: >200 nm). The results showed that the cargoes of PMEVs heterogeneous subpopulations which were released by PRP stimulated by PM0.1 were changed obviously. Moreover, compared with PEVs, PMEVs can lead to a decrease in the survival rate of Human Umbilical Vein Endothelial Cells (HUVECs). In PMEVs-S subpopulations, the alterations of lipids associated with membrane fusion and cell signaling transport (such as PC, Cer), as well as miRNAs related to inflammation, angiogenesis, and migration (miR-223, miR-22, miR-126, and miR-150), are similar to those in PMEVs-M subpopulations but distinct from PMEVs-L subpopulations. This study revealed the diverse communication mechanisms underlying PM0.1-induced cardiovascular injury, thereby offering potential avenues for the development of new biomarkers and therapeutic targets.

Arsenic aggravates the progression of diabetic nephropathy through miRNA-mRNA-autophagy axis

Environmental factors play an important role in the progression of diabetic nephropathy (DN), and previous study has shown that arsenic exposure can promote kidney damage in DN rats, however there is no relevant mechanism study so far. In this study, an arsenic-exposed (10 mg/L and 25 mg/L) DN mouse model was established through drinking water for 14 weeks. The results showed that 25 mg/L arsenic exposure increased the renal fibrosis in DN mice significantly, and urinary mAlb level increased with the increasing of arsenic exposure level. Transcriptome sequencing showed that autophagy-related pathways were significantly activated under the exposure dose of 25 mg/L, and levels of Beclin1 and p-ATG16L1/ATG16L1 were significantly higher in the 25 mg/L arsenic group compared to the control group. Silico analysis predicted the microRNAs those could regulate the hub genes of Mapk1, Rhoa and Cdc42, and dual-luciferase gene reporter assay was used to verify the targeted binding between these mRNAs and microRNAs. Our results suggested that high arsenic exposure could aggravate the progression of DN by altering autophagy, the miRNA-mRNA axles of let-7a-1-3p, let-7b-3p, let-7f-1-3p, miR-98-3p/Cdc42, Mapk1, Rhoa, could be considered promising targets to explore the mechanisms and therapeutic measures of DN after exposure to high levels of arsenic.

Analysis of the effects of β-mannanase on immune function and intestinal flora in broilers fed the low energy diet based on 16S rRNA sequencing and metagenomic sequencing

As an enzyme, β-mannanase (BM) can be widely used as feed additive to improve the growth performance of animals. This experiment aimed to determine the effect of the addition of BM to low-energy diet on the immune function and intestinal microflora of broiler chickens. In this study, 384 one-day-old Arbor Acres broilers were randomly divided into 3 groups (8 replicates per group): positive control (PC, received a corn-soybean meal basal diet), negative control (NC, received a low-energy diet with Metabolizable Energy (ME) reduced by 50 kcal/kg) and NC + BM group (NC birds + 100 mg/kg BM). All birds were raised for 42 d. The results showed that BM mitigated the damage of immune function in peripheral blood of broilers caused by the decrease of dietary energy level by increasing the Concanavalin A (Con A) index of stimulation (SI) and macrophages phagocytic activity in the peripheral blood of broilers at 42 d (P < 0.05). The analysis of cecum flora showed that the low-energy diet significantly reduced the observed_species index (P < 0.01), Chao1 index and ACE index (P < 0.05), which reduced the abundance and evenness of species in the cecum of broilers at 21 d. It also significantly reduced the relative abundance of Candidatus_Arthromitus and significantly increased the relative abundance of Pseudomonas in the cecum of broilers at 21 d, while also significantly increasing the relative abundance of Monoglobus at 42 d. BM significantly increased the relative abundance of Lachnospiraceae_UCG-001 and Lachnospiraceae_bacterium_615 in the cecum of broilers at 21 d. In addition, BM inhibited microbial Fatty acid degradation by decreasing the activity of glutaryl-CoA dehydrogenase. Collectively, BM could improve intestinal health by enhancing the immune function of broilers, promoting the proliferation of beneficial bacteria and reducing the number of harmful bacteria, regulating intestinal flora, thereby alleviating the adverse effects of lower dietary energy levels.

Cationic regulation of specificity and activity of defective MCo2O4 nanozyme (M=Fe, Co, Ni, Cu) for colorimetric detection of caffeic acid

Spinel oxide has great promise in constructing highly active nanozymes due to its tunable crystal structure. However, it still faces the problems of poor specificity and insufficient enzyme activity, which limits its application in the field of analysis. Herein, a series of transition metal spinel oxides were synthesized by cation regulation strategy, and their enzymatic activity and catalytic mechanism were analyzed. Interestingly, FeCo2O4, Co3O4 and NiCo2O4 had oxidase-like activity and peroxidase-like activity, while CuCo2O4 had specific and high oxidase-like activity. Their oxidase-like activities follow the order of FeCo2O4 < Co3O4 < NiCo2O4 < CuCo2O4, which is consistent with their cation radius. The smaller the cation radius of tetrahedral site, the more beneficial it is to increase the oxidase-like activity. The high oxidase-like activity of CuCo2O4 may be attributed to the production of 1O2, •O2- and •OH. EPR results showed the presence of abundant oxygen vacancies in CuCo2O4. Upon the introduction of EDTA, TMB color reaction fades because of oxygen vacancies elimination by EDTA, indicating that oxygen vacancies played an important role in the reaction. Based on the inhibition effect of caffeic acid on the high oxidase-like activity of CuCo2O4, a simple and sensitive caffeic acid colorimetric sensing platform was developed. The linear range for the detection of caffeic acid is 0.02-15 μM, with a detection limit as low as 13 nM. The constructed sensor enables the detection of caffeic acid in caffeic acid tablets and actual water samples, providing a new strategy for the detection of caffeic acid and drug quality control.

The accessible chromatin landscape of lipopolysaccharide-induced systemic inflammatory response identifying epigenome signatures and transcription regulatory networks in chickens

Lipopolysaccharide (LPS) can induce systemic inflammatory response (SIR) in animals. Understanding the regulatory mechanism of SIR and therapies to ensure healthy growth is urgently needed. Chromatin remodeling plays a crucial role in the expression of genes involved in immune diseases. In the present study, the ATAC-seq analysis revealed 3491 differential open chromatin sites in the spleen of chicks with SIR induced by LPS challenge, and we presented the motifs on these sites and the associated transcription factors. The regulatory network was presented by combining the differential open chromatin data with the mRNAs and exploded cytokines. Interestingly, the LPS challenge could regulate the mRNA expression of 202 genes through chromatin reprogramming, including critical genes such as TLE1 and JUN, which regulate signaling pathways such as I-κB kinase/NF-κB, Toll-like receptor, and downstream cytokine genes. Furthermore, dietary daidzein could inhibit DNA topoisomerase II, which reprograms the spatial conformation of chromatin in the inflammatory response and attenuates SIR. In conclusion, we successfully identified key genes directly regulated by chromatin reprogramming in SIR and demonstrated the chromatin epigenome signatures and transcriptional regulatory network, which provides an important reference for further research on avian epigenetics. There is great potential for alleviating SIR using dietary daidzein.

The impact of anxiety on gait impairments in Parkinson's disease: insights from sensor-based gait analysis

BACKGROUND

Sensor-based gait analysis provides a robust quantitative tool for assessing gait impairments and their associated factors in Parkinson's disease (PD). Anxiety is observed to interfere with gait clinically, but this has been poorly investigated. Our purpose is to utilize gait analysis to uncover the effect of anxiety on gait in patients with PD.

METHODS

We enrolled 38 and 106 PD patients with and without anxiety, respectively. Gait parameters were quantitively examined and compared between two groups both in single-task (ST) and dual-task (DT) walking tests. Multiple linear regression was applied to evaluate whether anxiety independently contributed to gait impairments.

RESULTS

During ST, PD patients with anxiety presented significantly shorter stride length, lower gait velocity, longer stride time and stance time, longer stance phase, smaller toe-off (TO) and heel-strike (HS) angles than those without anxiety. While under DT status, the differences were diminished. Multiple linear regression analysis demonstrated that anxiety was an independent factor to a serials of gait parameters, particularly ST-TO (B = -2.599, (-4.82, -0.38)), ST-HS (B = -2.532, (-4.71, -0.35)), ST-TO-CV (B = 4.627, (1.71, 7.64)), ST-HS-CV(B = 4.597, (1.66, 7.53)), ST stance phase (B = 1.4, (0.22, 2.58)), and DT stance phase (B = 1.749, (0.56, 2.94)).

CONCLUSION

Our study discovered that anxiety has a significant impact on gait impairments in PD patients, especially exacerbating shuffling steps and prolonging stance phase. These findings highlight the importance of addressing anxiety in PD precision therapy to achieve better treatment outcomes.

Effect of acupuncture combined with Ningshen mixture on climacteric insomnia: A randomized controlled trial

BACKGROUND

In recent years, the incidence of menopause insomnia has gradually increased, seriously affecting women's physical and mental health.

METHODS

Total 82 climacteric insomnia patients received from January 2021 to January 2023 were divided into 2 groups at random. In control group, 41 cases received conventional Western medicine, and in study group, 41 cases received acupuncture combined with Ningshen mixture. Clinical effectiveness of both groups was compared, neurotransmitter levels, TCM syndrome integral and Pittsburgh Sleep Quality Index (PSQI) were assessed in both groups. Meanwhile, the recurrence rate and safety were evaluated in 2 groups.

RESULTS

The curative effect in study group was better than that in control group (P < .05). After treatment, the expressions of 5-hydroxytryptamine and β-endorphin (β-EP) in study group were higher than control group (P < .05); TCM syndrome scores and PSQI scores in study group were lower than control group (P < .05). The total recurrence rate in study group was obviously lower than control group at 3 months after treatment (P < .05). There were no serious adverse reactions in both group, and no distinct difference between 2 groups was found (P > .05).

CONCLUSION

Acupuncture united with Ningshen mixture has a significant therapeutic effect and high safety in climacteric insomnia patients. It can effectively improve the neurotransmitter levels, clinical symptoms and sleep quality, and reduce the recurrence rate of climacteric insomnia patients, which has high clinical application value and is worthy of clinical promotion.

Deficiency of betaine-homocysteine methyltransferase activates glucose-6-phosphate dehydrogenase (G6PD) by decreasing arginine methylation of G6PD in hepatocellular carcinogenesis

Betaine-homocysteine methyltransferase (BHMT) regulates protein methylation and is correlated with tumorigenesis; however, the effects and regulation of BHMT in hepatocarcinogenesis remain largely unexplored. Here, we determined the clinical significance of BHMT in the occurrence and progression of hepatocellular carcinoma (HCC) using tissue samples from 198 patients. BHMT was to be frequently found (86.6%) expressed at relatively low levels in HCC tissues and was positively correlated with the overall survival of patients with HCC. Bhmt overexpression effectively suppressed several malignant phenotypes in hepatoma cells in vitro and in vivo, whereas complete knockout of Bhmt (Bhmt-/-) produced the opposite effect. We combined proteomics, metabolomics, and molecular biological strategies and detected that Bhmt-/- promoted hepatocarcinogenesis and tumor progression by enhancing the activity of glucose-6-phosphate dehydrogenase (G6PD) and PPP metabolism in DEN-induced HCC mouse and subcutaneous tumor-bearing models. In contrast, restoration of Bhmt with an AAV8-Bhmt injection or pharmacological inhibition of G6PD attenuated hepatocarcinogenesis. Additionally, coimmunoprecipitation identified monomethylated modifications of the G6PD, and BHMT regulated the methylation of G6PD. Protein sequence analysis, generation and application of specific antibodies, and site-directed mutagenesis indicated G6PD methylation at the arginine residue 246. Furthermore, we established bidirectionally regulated BHMT cellular models combined with methylation-deficient G6PD mutants to demonstrate that BHMT potentiated arginine methylation of G6PD, thereby inhibiting G6PD activity, which in turn suppressed hepatocarcinogenesis. Taken together, this study reveals a new methylation-regulatory mechanism in hepatocarcinogenesis owing to BHMT deficiency, suggesting a potential therapeutic strategy for HCC treatment.

Observation of Structures in the Processes e^{+}e^{-}→ωχ_{c1} and ωχ_{c2}

We present measurements of the Born cross sections for the processes e^{+}e^{-}→ωχ_{c1} and ωχ_{c2} at center-of-mass energies sqrt[s] from 4.308 to 4.951 GeV. The measurements are performed with data samples corresponding to an integrated luminosity of 11.0  fb^{-1} collected with the BESIII detector operating at the Beijing Electron Positron Collider storage ring. Assuming the e^{+}e^{-}→ωχ_{c2} signals come from a single resonance, the mass and width are determined to be M=(4413.6±9.0±0.8)  MeV/c^{2} and Γ=(110.5±15.0±2.9)  MeV, respectively, which is consistent with the parameters of the well-established resonance ψ(4415). In addition, we also use one single resonance to describe the e^{+}e^{-}→ωχ_{c1} line shape and determine the mass and width to be M=(4544.2±18.7±1.7)  MeV/c^{2} and Γ=(116.1±33.5±1.7)  MeV, respectively. The structure of this line shape, observed for the first time, requires further understanding.

UV-aged polystyrene nanoplastics aggravate intestinal barrier damage by overproduction of ROS

UV irradiation significantly alters nanoplastics (NPs) physicochemical properties, thus affecting their biological toxicity. This study is the first to assess the influence of virgin and UV-aged polystyrene NPs (v-PS NPs, a-PS NPs) on the intestinal barrier of ICR mice. We found that a-PS NPs can cause more severe intestinal barrier damage compared with v-PS NPs. The reason may be attributed to that a-PS NPs produced more ROS in intestinal tissue. Moreover, the strong oxidizing property of hydroxyl radicals (·OH) generated from the a-PS NPs can damage cell membranes through lipid peroxidation, thereby leading to a low clearance rate of ·OH due to the impaired intestinal tissue function, in turn, causing more ROS to accumulate and inducing severe oxidative damage. This research underscores the crucial role of ·OH in mediating oxidative damage from UV-aged nanoparticles, emphasizing the need to consider environmental factors in assessing NPs toxicity.

Insight into the structural characteristics of self-assembled liposome with epigallocatechin gallate/alcohol dehydrogenase

In this study, the encapsulation and structural characteristics of the self-assembled liposome formed by epigallocatechin gallate (EGCG) and alcohol dehydrogenase (ADH) were studied. According to the results, EGCG significantly increased the catalytic activity of ADH with a 33.33 % activation rate and the liposomes were able to entrap EGCG-ADH with an effectiveness of 88.94 %. The self-assembled monolayers had nanometer-sized particles, and the excellent self-assembled system was demonstrated by the low PDI value and high surface absolute potential. The scanning electron microscope showed that the self-assembled liposome was honeycomb, groove-shaped, and rough. The spectroscopic results showed that EGCG-ADH complex was formed through hydrogen bond, which changed the secondary structure of the liposome, and verified EGCG-ADH liposome system was successfully prepared. In vitro digestion experiments showed that the gastrointestinal tolerance and antioxidant activity of EGCG-ADH liposomes were significantly higher than those of free EGCG-ADH.

Coupled-Channel Analysis of the χ_{c1}(3872) Line Shape with BESIII Data

We perform a study of the χ_{c1}(3872) line shape using the data samples of e^{+}e^{-}→γχ_{c1}(3872), χ_{c1}(3872)→D^{0}D[over ¯]^{0}π^{0}, and π^{+}π^{-}J/ψ collected with the BESIII detector. The effects of the coupled channels and the off-shell D^{*0} are included in the parametrization of the line shape. The line shape mass parameter is obtained to be M_{X}=(3871.63±0.13_{-0.05}^{+0.06})  MeV. Two poles are found on the first and second Riemann sheets corresponding to the D^{*0}D[over ¯]^{0} branch cut. The pole location on the first sheet is much closer to the D^{*0}D[over ¯]^{0} threshold than the other, and is determined to be 7.04±0.15_{-0.08}^{+0.07}  MeV above the D^{0}D[over ¯]^{0}π^{0} threshold with an imaginary part -0.19±0.08_{-0.19}^{+0.14}  MeV.

Observation of the Anomalous Shape of X(1840) in J/ψ→γ3(π^{+}π^{-}) Indicating a Second Resonance Near pp[over ¯] Threshold

Using a sample of (10087±44)×10^{6}  J/ψ events, which is about 45 times larger than that was previously analyzed, a further investigation on the J/ψ→γ3(π^{+}π^{-}) decay is performed. A significant distortion at 1.84  GeV/c^{2} in the line shape of the 3(π^{+}π^{-}) invariant mass spectrum is observed for the first time, which could be resolved by two overlapping resonant structures, X(1840) and X(1880). The new state X(1880) is observed with a statistical significance larger than 10σ. The mass and width of X(1880) are determined to be 1882.1±1.7±0.7  MeV/c^{2} and 30.7±5.5±2.4  MeV, respectively, which indicates the existence of a pp[over ¯] bound state.

Promoting oxygen vacancies utility for tetracycline degradation via peroxymonosulfate activation by reduced Mg-doped Co3O4: Kinetics and key role of electron transfer pathway

Developing cobalt-based catalysts with a high abundance of oxygen vacancies (Vo) and exceptional Vo utility efficiency for the prompt removal of stubborn contaminants through peroxymonosulfate (PMS) activation poses a significant challenge. Herein, we reported the synthesis of the reduced Mg-doped Co3O4 nanosheets, i.e. Mg-doped Co3O4-r, via Mg doping and followed by NaBH4 reduction, aiming to degrade tetracycline (TC). Various characterization results illustrated that NaBH4 reduction imparted higher Vo utility efficiency to Mg-doped Co3O4-r, along with an ample presence of reduced Co2+ species and an increased surface area, thereby substantially elevating PMS activation capability. Notably, Mg-doped Co3O4-r achieved more than 97.9% degradation of 20 mg/L TC within 10 min, showing an over 8-fold increase in reaction rate relative to the Mg-doped Co3O4 (kobs: 0.3285 min-1 vs 0.0399 min-1). The high removal efficiency of TC was sustained across a broad pH range of 3-11, even in the presence of common anions and humic acid. Radical quenching trials, EPR outcomes, and electrochemical analysis indicated that neither radicals nor 1O2 were the primary active species. Instead, electron transfer pathway played a dominant role in TC degradation. The Mg-doped Co3O4-r displayed excellent recyclability and versatility. Even after the fifth cycle, it maintained an impressive 83.0% removal of TC. Furthermore, it exhibited rapid degradation capabilities for various pollutants, including levofloxacin, pefloxacin, ciprofloxacin, malachite green, and rhodamine B. The TC degradation pathway was proposed based on LC-MS determination of its degradation intermediates. This study showcases an innovative strategy for the rational design of an efficient cobalt-based activator, leveraging electron transfer pathways through PMS activation to degrade antibiotics effectively.

NFKBIZ regulates NFκB signaling pathway to mediate tumorigenesis and metastasis of hepatocellular carcinoma by direct interaction with TRIM16

Hepatocellular carcinoma (HCC) is a malignant tumor with high incidence and mortality rates. NFKBIZ, a member of the nuclear factor kappa B inhibitory family, is closely related to tumor progression. However, the precise role of NFKBIZ in HCC remains unclear. To explore this, we conducted a series of experiments from clinic to cells. Western blot and qPCR revealed a significant downregulation of NFKBIZ in human HCC tissues. Clinical character analysis showed that the patients with lower NFKBIZ expression had poorer prognosis and higher clinical stage. By using CCK-8, wound healing, transwell invasion and migration assay, we discovered that NFKBIZ expression was reversely associated with the proliferation, invasion, and migration ability of HCC cells in vitro. Additionally, the results obtained from xenograft assay and lung metastasis models showed that NFKBIZ overexpression inhibited the growth and metastasis of HCC cells in vivo. Western blot and immunofluorescence assay further revealed that NFKBIZ mediated HCC cell growth and migration by regulating NFκB signaling transduction. Finally, flow cytometry, protein degradation assay and Co-immunoprecipitation indicated that TRIM16 can enhance NFKBIZ ubiquitination by direct interactions at its K48 site, which may thereby alleviate HCC cell apoptosis to induce the insensitivity to sorafenib. In conclusion, our study demonstrated that NFKBIZ regulated HCC tumorigenesis and metastasis by mediating NFκB signal transduction and TRIM16/NFKBIZ/NFκB axis may be the underlying mechanism of sorafenib insensitivity in HCC.

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

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

Insight into the binding characteristics of epigallocatechin-3-O-gallate and alcohol dehydrogenase: Based on the spectroscopic and molecular docking analysis

Alcohol dehydrogenase (ADH) is one of the pivotal enzymes for alcohol metabolism, which plays an important role in many physiological processes. In this study, the activation effects of epigallocatechin-3-O-gallate (EGCG) on ADH and the characteristics of the interaction were investigated via biochemical method, spectroscopy methods, and molecular docking. The results demonstrated that EGCG significantly increased the catalytic activity of ADH with a 33.33% activation rate and that EGCG blending slightly altered the microenvironment surrounding ADH aromatic amino acids, with an increase in the quantity of β-sheet and a decrease in the α-helix. Through the thermal stability analysis, it is further shown that the interaction of the two affects the intra-molecular hydrogen bond formation of the protein, and the conformation is partially extended. Besides, a total of 8 residues in ADH participated in the docking with EGCG, among which Asp-227, Lys-231, Glu-234, Gly-365 and Glu-366 participated in the formation of hydrogen bonds. At the same time, EGCG and amino group of Lys-231 form a noncovalent bond through cation-π interaction. In particular, hydrogen bonding was beneficial to keep the stability of EGCG-ADH, which was the primary driver of ADH activity activation. The results supply a new way for EGCG to activate ADH and a theoretical basis for the development of anti-alcoholism products.

Evolution and chemical diversity of the volatile compounds in Salvia species

INTRODUCTION

The plant essential oils are composed of volatile compounds and have significant value in preventing and treating neurological diseases, anxiety, depression, among others. The genus Salvia has been shown to be an important medicinal resource, especially the aerial parts of genus Salvia, which are rich in volatile compounds; however, the chemical diversity and distribution patterns of volatile compounds in Salvia species are still unknown.

OBJECTIVE

The work is performed to analyse the chemical diversity and distribution patterns of volatile compounds in genus Salvia.

METHODS

The genomic single nucleotide polymorphisms (SNPs) combined with gas chromatography-mass spectrometry (GC-MS) were used to explore the evolution and chemical diversity of Salvia volatile compounds. Initially, the genetic relationship of genus Salvia was revealed by phylogenetic tree that was constructed based on SNPs. And then, GC-MS was applied to explore the chemical diversity of volatile compounds.

RESULTS

The results indicated that the volatile compounds were mainly monoterpenoids, sesquiterpenoids, and aliphatic compounds. The genomic SNPs divided species involved in this work into four branches. The volatile compounds in the first and second branches were mainly sesquiterpenoids and monoterpenoids, respectively. Species in the third branch contained more aliphatic compounds and sesquiterpenoids. And those in the fourth branch were also rich in monoterpenoids but had relatively simple chemical compositions.

CONCLUSION

This study offered new insights into the phylogenetic relationships besides chemistry diversity and distribution pattern of volatile compounds of genus Salvia, providing theoretical guidance for the investigations and development of secondary metabolites.

Data-Driven Tunnel Oxide Passivated Contact Solar Cell Performance Analysis Using Machine Learning

Tunnel oxide passivated contacts (TOPCon) have gained interest as a way to increase the energy conversion efficiency of silicon solar cells, and the International Technology Roadmap of Photovoltaics forecasts TOPCon to become an important technology despite a few remaining challenges. To review the recent development of TOPCon cells, this work has compiled a dataset of all device data found in current literature, which sums up to 405 devices from 131 papers. This may seem like a surprisingly small number of cells given the recent interest in the TOPCon architecture, but it illustrates a problem of data dissemination in the field. Notwithstanding the limited number of cells, there is a great diversity in cell manufacturing procedures, and this work observes a gradual increase in performance indicating that the field has not yet converged on a set of best practices. By analyzing the data using statistical methods and machine learning (ML) algorithms, this work is able to reinforces some commonly held hypotheses related to the performance differences between different device architectures. This work also identifies a few more unintuitive feature combinations that would be of interest for further experimentally studies. This work also aims to inspire improvements in data management and dissemination within the TOPCon community.

KAT2A-mediated succinylation modification of notch1 promotes the proliferation and differentiation of dental pulp stem cells by activating notch pathway

BACKGROUND

Dental pulp stem cells (DPSCs) are a kind of undifferentiated dental mesenchymal stem cells with strong self-renewal ability and multi-differentiation potential. This study aimed to investigate the regulatory functions of succinylation modification in DPSCs.

METHODS

DPSCs were isolated from the dental pulp collected from healthy subjects, and then stem cell surface markers were identified using flow cytometry. The osteogenic differentiation ability of DPSCs was verified by alkaline phosphatase (ALP) and alizarin red staining methods, while adipogenic differentiation was detected by oil red O staining. Meanwhile, the mRNA of two desuccinylases (SIRT5 and SIRT7) and three succinylases (KAT2A, KAT3B, and CPT1A) in DPSCs before and after mineralization induction were detected using quantitative real-time PCR. The cell cycle was measured by flow cytometry, and the expression of bone-specific genes, including COL1a1 and Runx2 were evaluated by western blotting and were combined for the proliferation and differentiation of DPSCs. Co-immunoprecipitation (co-IP) and immunofluorescence were combined to verify the binding relationship between proteins.

RESULTS

The specific markers of mesenchymal stem cells were highly expressed in DPSCs, while the osteogenic differentiation ability of isolated DPSCs was confirmed via ALP and alizarin red staining. Similarly, the oil red O staining also verified the adipogenic differentiation ability of DPSCs. The levels of KAT2A were found to be significantly upregulated in mineralization induction, which significantly decreased the ratio of G0/G1 phase and increased S phase cells; converse results regarding cell cycle distribution were obtained when KAT2A was inhibited. Moreover, overexpression of KAT2A promoted the differentiation of DPSCs, while its inhibition exerted the opposite effect. The elevated KAT2A was found to activate the Notch1 signaling pathway, which succinylated Notch1 at the K2177 site to increase their corresponding protein levels in DPSCs. The co-IP results showed that KAT2A and Notch1 were endogenously bound to each other, while inhibition of Notch1 reversed the effects of KAT2A overexpression on the DPSCs proliferation and differentiation.

CONCLUSION

KAT2A interacted directly with Notch1, succinylating the Notch1 at the K2177 site to increase their corresponding protein levels in DPSCs. Similarly, KAT2A-mediated succinylation modification of Notch1 promotes the DPSCs proliferation and differentiation, suggesting that targeting KAT2A and Notch1 may contribute to tooth regeneration.

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

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

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

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

Key Words Collapse

MESH Headings Collapse

Grants Collapse

Affiliation(s)

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

Collapse

Recalled age of myopia onset may predict risk of high adult myopia in Chinese adults

INTRODUCTION

This study aimed to investigate the relationship between age of myopia onset and high myopia and to explore if age of onset mediated the associations of high myopia with parental myopia and time spent on electronics.

METHODS

This cross-sectional study enrolled 1118 myopic patients aged 18 to 40. Information was obtained via a detailed questionnaire. Multivariable logistic regression and linear regression models were utilized to assess age of onset in relation to high myopia and spherical equivalent refractive error, respectively. Structural equation models examined the mediated effect of onset age on the association between parental myopia, time spent on electronics and high myopia.

RESULTS

An early age at myopia onset was negatively correlated with spherical equivalent refractive power. Subjects who developed myopia before the age of 12 were more likely to suffer from high myopia than those who developed myopia after the age of 15. Age of myopia onset was the strongest predictor of high myopia, with an area under the curve (AUC) in Receiver Operator Characteristic (ROC) analysis of 0.80. Additionally, age of myopia onset served as a mediator in the relationships between parental myopia, electronic device usage duration, and the onset of high myopia in adulthood.

CONCLUSIONS

Age of myopia onset might be the single best predictor for high myopia, and age at onset appeared to mediate the associations of high myopia with parental myopia and time spent on electronics.

Development of high-efficiency superparamagnetic drug delivery system with MPI imaging capability

In this study, a high-efficiency superparamagnetic drug delivery system was developed for preclinical treatment of bladder cancer in small animals. Two types of nanoparticles with magnetic particle imaging (MPI) capability, i.e., single- and multi-core superparamagnetic iron oxide nanoparticles (SPIONs), were selected and coupled with bladder anti-tumor drugs by a covalent coupling scheme. Owing to the minimal particle size, magnetic field strengths of 270 mT with a gradient of 3.2 T/m and 260 mT with a gradient of 3.7 T/m were found to be necessary to reach an average velocity of 2 mm/s for single- and multi-core SPIONs, respectively. To achieve this, a method of constructing an in vitro magnetic field for drug delivery was developed based on hollow multi-coils arranged coaxially in close rows, and magnetic field simulation was used to study the laws of the influence of the coil structure and parameters on the magnetic field. Using this method, a magnetic drug delivery system of single-core SPIONs was developed for rabbit bladder therapy. The delivery system consisted of three coaxially and equidistantly arranged coils with an inner diameter of Φ50 mm, radial height of 85 mm, and width of 15 mm that were positioned in close proximity to each other. CCK8 experimental results showed that the three types of drug-coupled SPION killed tumor cells effectively. By adjusting the axial and radial positions of the rabbit bladder within the inner hole of the delivery coil structure, the magnetic drugs injected could undergo two-dimensional delivery motions and were delivered and aggregated to the specified target location within 12 s, with an aggregation range of about 5 mm × 5 mm. In addition, the SPION distribution before and after delivery was imaged using a home-made open-bore MPI system that could realistically reflect the physical state. This study contributes to the development of local, rapid, and precise drug delivery and the visualization of this process during cancer therapy, and further research on MPI/delivery synchronization technology is planned for the future.

Enhancing Ultraviolet Stability and Performance of Wide Bandgap Perovskite Solar Cells Through Ultraviolet Light-Absorbing Passivator

Ultraviolet light (UV) has caused tremendous damage to perovskite solar cells (PSCs), degrading the perovskite and shortening their lifetime. Defects act as non-radiative recombination sites, accelerate the degradation process, reduce the efficiency of the device and weaken the stability of solar cell. In this work, to realize efficient and stable p-i-n wide bandgap solar cells under UV, a synergetic strategy utilizing UV light-absorbing passivator, (Trifluoroacetyl) benzotriazole (TFABI), enhance UV photostability and regulate the defect passivation is proposed. By using TFABI, the degradation of the perovskite absorption layer under UV light is suppressed, spectral response is enhanced and the Pb vacancy defects are passivated. As a result, the target device achieves an efficiency of 21.54%, exhibiting excellent long-term stability under 365 nm UV irradiation. After 60 h of irradiation, it retains 85% of its initial value (60 mW cm-2 , RH 25-30%, 25 °C).

Comparison of Efficacy and Adherence of Patient-Preferred (1 Unit Daily) and ADA/EASD Guideline-Recommended (2 Units Every 3 Days) Basal Insulin Titration Algorithms: Multicenter, Randomized, Clinical Study

Aim

Insulin titration often faces inertia, hindering glycemic control. A patient-centered approach empowers patients to overcome this inertia. This study aims to compare the effectiveness of patient-preferred and guideline-recommended self-titration algorithms in achieving glycemic targets and improving adherence.

Methods

Outpatients with type 2 diabetes (T2D) who did not respond to oral antihyperglycemic drugs (OAD) were assessed. They were randomly assigned to patient-preferred and guideline-recommended groups. In the patient-preferred group, individuals selected an algorithm to self-adjust their insulin glargine dosage by 2 units every 3 days if the mean fasting blood glucose (FBG) over the past 3 consecutive days was ≥7.0 mmol/L, or by 1 unit daily if the FBG on the same day was ≥7.0 mmol/L. In the guideline-recommended group, insulin glargine was titrated by 2 units every 3 days if the mean FBG over the past 3 consecutive days was ≥7.0 mmol/L. The FBG target was set below <7.0 mmol/L.

Results

Thirty-nine participants in the patient-preferred group and 42 in the guideline-recommended group completed the study. The cumulative rates of achieving the FBG target in the patient-preferred group compared to the guideline-recommended group were 69.2% vs 54.8% (χ²=1.792, p=0.181) in week 1, 89.7% vs 73.8% (χ²=3.403, p = 0.065) in week 2, 94.9% vs 76.2% (χ²=17.638, p=0.000) in week 3, and 100.0% vs 88.1% (χ²=4.405, p=0.036) in week 4. Adherence rates were significantly higher in the patient-preferred group (97.4%, 37/38) compared to the guideline-recommended group (66.7%, 28/42) (χ²=12.688, p=0.000). Insulin glargine dosage at FBG target achievement was 21.2±4.3 U in the patient-preferred group and 18.8±6.7 U in the guideline-recommended group (t=1.888, p=0.063). Hypoglycemia was reported in 1 patient in the guideline-recommended group, with no instances in the patient-preferred group.

Conclusion

The patient-preferred self-titration algorithm demonstrates a higher rate of reaching glucose targets and improved adherence.

Trial Registration Number

ChiCTR2100050805.

Unveiling the distribution of chemical constituents at different body parts and maturity stages of Ganoderma lingzhi by combining metabolomics with desorption electrospray ionization mass spectrometry imaging (DESI)

Ganoderma lingzhi is an important medicinal fungus, which is widely used as dietary supplement and for pharmaceutical industries. However, the spatial distribution and dynamic accumulation pattern of active components such as ganoderic acids (GAs) among different parts of G. lingzhi fruiting body are still unclear. In this study, desorption electrospray ionization mass spectrometry imaging (DESI-MSI) with untargeted metabolomics analysis was applied to investigate the metabolites distribution within G. lingzhi fruiting body at four different maturity stages (squaring, opening, maturation and harvesting stage). A total of 132 metabolites were characterized from G. lingzhi, including 115 triterpenoids, 11 fatty acids and other component. Most of the GAs content in the cap was significantly higher than that in the stipe, with six components such as ganoderic acid B being extremely significant. GAs in the cap was mainly present in the bottom edge of the mediostratum layer, such as ganoderic A-I and ganoderic GS-1, while in the stipe, they were mainly distributed in the shell layer and the context layer, such as ganoderic A-F. Most ganoderic acids content in both the stipe and the cap of G. lingzhi was gradually decreased with the development of G. lingzhi. The GAs in the stipe was gradually transferred from the shell layer to the content layer, while the distribution of GAs among different tissues of the cap was not significantly changed. In addition, linoleic acid, 9-HODE, 9-KODE and other fatty acids were mainly accumulated in the opening and maturing stage of the caps. This study further clarifies the spatial dynamic distribution of GAs in G. lingzhi fruiting body at four different maturity stages (squaring, opening, maturation and harvesting stage), which provides a basis for the rational utilization of the medicinal parts of G. lingzhi. Furthermore, mass spectrometry imaging combined with non-target metabolome analysis provides a powerful tool for the spatial distribution of active substances in the different regions of the medicinal edible fungi.

[Changes in OCTA-related parameters and their impact on retinal sensitivity after ILM flap inversion surgery in patients with IMH]

Objective: To analyze the changes in optical coherence tomography angiography(OCTA)-related parameters before and after idiopathic macular hole (IMH) internal limiting membrane (ILM) flap inversion surgery and assess their impact on retinal sensitivity. Methods: A retrospective case series study was conducted, collecting clinical data of 30 patients (30 eyes) diagnosed with IMH who underwent vitrectomy combined with ILM flap inversion surgery at Shanxi Eye Hospital, affiliated with Shanxi Medical University, between January 2020 and December 2021. Visual acuity and best-corrected visual acuity were examined preoperatively and at 1, 3, and 6 months postoperatively. Microperimetry measured retinal sensitivity (RS), and OCTA measured retinal thickness (RT) as well as vessel density (VD) in the superficial capillary plexus (SCP) and deep capillary plexus (DCP). Statistical analysis was performed using t-tests, repeated measures analysis of variance, and Pearson correlation analysis. Results: Thirty patients with IMH (30 eyes) were included, with 3 males (3 eyes) and 27 females (27 eyes). The mean age was (62.5±3.0) years, and the follow-up time was (96.3±1.3) days, with a 100% closure rate of macular holes postoperatively. RT in the macular was significantly lower at 1, 3, and 6 months postoperatively compared to preoperative values (F=46.21, P<0.001). The RT in the upper macular region showed statistically significant differences at different time points (P<0.001). VD in the SCP layer showed no significant differences between the upper and lower macular regions at various time points (F=3.21, P=0.601). VD in the upper region of the DCP layer increased at 1, 3, and 6 months postoperatively (P<0.001). RS in the macular was higher at 1, 3, and 6 months postoperatively compared to preoperative values (F=52.01, P<0.001). RS in the lower macular region increased at 3 and 6 months postoperatively (P<0.001), while in the upper region, it increased only at 6 months postoperatively (P<0.001). There was a positive correlation between RS and RT at 1 and 3 months postoperatively, but not at 6 months postoperatively in the upper macular region (r=0.40, P=0.071). In the lower macular region, there was a positive correlation between RS and RT at 1 and 3 months postoperatively (P<0.001). There was no correlation between RS in the upper macular region at 6 months postoperatively and preoperative RT (r=0.43, P=0.072), but there was a positive correlation with RT at 3 months postoperatively (r=0.58, P=0.041). Conclusions: After idiopathic macular hole internal limiting membrane flap inversion surgery, the OCTA-related parameters have changed. There are transient changes in deep vascular parameters and thinning of the retinal layers at the ILM inversion site, leading to decreased sensitivity.

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.

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

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

Copper removal from aqueous solutions by white rot fungus Pleurotus ostreatus GEMB-PO1 and its potential in co-remediation of copper and organic pollutants

Addressing the environmental contamination from heavy metals and organic pollutants remains a critical challenge. This study explored the resilience and removal potential of Pleurotus ostreatus GEMB-PO1 for copper. P. ostreatus GEMB-PO1 showed significant tolerance, withstanding copper concentrations up to 2 mM. Its copper removal efficiency ranged from 64.56 % at 0.5 mM to 22.90 % at 8 mM. Transcriptomic insights into its response to copper revealed a marked upregulation in xenobiotic degradation-related enzymes, such as laccase and type II peroxidases. Building on these findings, a co-remediation system using P. ostreatus GEMB-PO1 was developed to remove both copper and organic pollutants. While this approach significantly enhanced the degradation efficiency of organic contaminants, it concurrently exhibited a diminished efficacy in copper removal within the composite system. This study underscores the potential of P. ostreatus GEMB-PO1 in environmental remediation. Nevertheless, further investigation is required to optimize the simultaneous removal of organic pollutants and copper.

Mannanase improves the growth performance of broilers by alleviating inflammation of the intestinal epithelium and improving intestinal microbiota

This experiment aimed to discuss and reveal the effect and mechanism of mannanase on intestinal inflammation in broilers triggered by a soybean meal diet. In this experiment, 384 Arbor Acres broilers at 1 d old were randomly divided into 3 treatment groups. The broilers were fed a corn-soybean meal basal diet, a low-energy diet (metabolizable energy reduced by 50 kcal/kg), and a low-energy diet supplemented with 100 mg/kg mannanase for 42 d. The low-energy diet increased feed conversion ratio from 0 to 42 d, reduced ileal villus height and villus height-to-crypt depth ratio and upregulated the expression of nuclear factor kappa B (NF-κB) in the ileum (P < 0.05). It also reduced cecal short-chain fatty acids (SCFA), such as acetic acid (P < 0.05). Compared with low-energy diets, the addition of mannanase increased body weight at 42 d, promoted the digestibility of nutrients, and maintained the morphology and integrity of the intestinal epithelium of broilers (P < 0.05). In addition, mannanase upregulated the expression of claudin-1 (CLDN1) and zonula occludens-1 (ZO-1) in the jejunum at 21 d, downregulated the expression of ileal NF-κB, and increased the content of isobutyric acid in the cecum of broilers (P < 0.05). The results for the ileal microbiota showed that a low-energy diet led to a decrease in the relative abundance of Lactobacillus reuteri in the ileum of broilers. The addition of mannanase increased the relative abundance of Lactobacillus-KC45b and Lactobacillus johnsonii in broilers. Furthermore, a low-energy diet reduced the relative abundance of Butyricicoccus in the intestine of broilers and inhibited oxidative phosphorylation and phosphoinositol metabolism. Mannanase increased the relative abundance of Odoribacter, promoted energy metabolism and N-glycan biosynthesis, and increased the activities of GH3 and GH18. It is concluded that mannanase could improve the growth performance of broilers by reducing the expression of NF-κB in the ileum, increasing the production of SCFA in the cecum, suppressing intestinal inflammation, balancing the intestinal microbiota, reducing damage to the intestinal barrier, and improving the efficiency of nutrient utilization to alleviate the adverse effects caused by the decrease in dietary energy level.

Reliability and stability of ultrasound-guided attenuation parameter in evaluating hepatic steatosis

PURPOSE

This study aimed to explore the reliability and stability of ultrasound-guided attenuation parameter (UGAP) values obtained by two measuring methods and different measuring times.

METHODS

Patients who underwent liver UGAP examinations in our hospital from September 2022 to December 2022 were retrospectively analyzed. The clinical data and UGAP measurements results were collected. Two different measuring methods: static single-frame multi-point measuring and dynamic multi-frame single-point measuring, were performed for each patient, and 10 UGAP values of each measuring method were recorded. The medians of the UGAP values of the 1st-3rd, 1st-5th, 1st-7th and 1st-10th by each measuring method were taken as the final UGAP values of measuring 3, 5, 7 and 10 times. The UGAP values obtained by the two different measuring methods and different measuring times (3, 5, 7 or 10 times) were compared.

RESULTS

206 patients were included in this study. There was no statistical difference between UGAP values measured by static single-frame multi-point measuring and dynamic multi-frame single-point measuring (P = 0.689, P = 0.270, P = 0.298, P = 0.091), regardless of measuring times (3, 5, 7, 10 times). No significant difference between the UGAP values obtained by 3, 5, 7 and 10 measurements was found (P = 0.554, P = 0.916).

CONCLUSION

The UGAP values obtained by the two different measuring methods and different measuring times (3, 5, 7 and 10 times) are stable and reliable. Additionally, 3 times of UGAP measurements might be enough for each patient in clinical practice.

Cyy-287, a novel pyrimidine-2,4-diamine derivative, efficiently mitigates inflammatory responses, fibrosis, and lipid synthesis in obesity-induced cardiac and hepatic dysfunction

Background

Inflammation and metabolic disorders are important factors in the occurrence and development of obesity complications. In this study, we investigated the protective effect and underlying mechanism of a novel pyrimidine-2,4-diamine derivative, Cyy-287, on mice fed a high-fat diet (HFD).

Methods

The mice were randomly separated into four groups (n ≥ 7): control (regular diet), HFD, HFD with Cyy-287 (5 mg/kg), and HFD with Cyy-287 (20 mg/kg) following HFD feeding for 10 weeks. After a 10-week administration, ALT and AST enzymes, echocardiography, immunohistochemical (IHC), Western blot (WB), Masson and Sirius Red staining were used to evaluate functional and morphological changes to the heart and liver. Microsomes from the mouse liver were extracted to quantify the total amount of CYP450 enzymes after drug treatment.

Results

Cyy-287 decreased the levels of serum glucose, LDL, TC, ALT, and AST activities in HFD-treated mice. However, Cyy-287 administration increased ejection fraction (EF) and fractional shortening (FS) index of the heart. Cyy-287 inhibited histopathological changes in the heart and liver; decreased inflammatory activity; significantly diminished p38 mitogen-activated protein kinase (MAPK), the nuclear factor-kappa B (NF-κB) axis, and sterol regulatory element-binding protein-1c (SREBP-1c); and upregulated the AMP-activated protein kinase (AMPK) pathway in HFD-treated mice. Cyy-287 restored the content of hepatic CYP450 enzymes.

Conclusion

These findings demonstrated that Cyy-287 protected heart and liver cells from obesity-induced damage by inhibiting inflammation, fibrosis, and lipid synthesis.

Cross-subject EEG-based emotion recognition through dynamic optimization of random forest with sparrow search algorithm

The objective of EEG-based emotion recognition is to classify emotions by decoding signals, with potential applications in the fields of artificial intelligence and bioinformatics. Cross-subject emotion recognition is more difficult than intra-subject emotion recognition. The poor adaptability of classification model parameters is a significant factor of low accuracy in cross-subject emotion recognition. We propose a model of a dynamically optimized Random Forest based on the Sparrow Search Algorithm (SSA-RF). The decision trees number (DTN) and the leave minimum number (LMN) of the RF are dynamically optimized by the SSA. 12 features are used to construct feature combinations for selecting the optimal feature combination. DEAP and SEED datasets are employed for testing the performance of SSA-RF. The experimental results show that the accuracy of binary classification is 76.81% on DEAP, and the accuracy of triple classification is 75.96% on SEED based on SSA-RF, which are both higher than that of traditional RF. This study provides new insights for the development of cross-subject emotion recognition, and has significant theoretical value.

Syntrichia ruralis: emerging model moss genome reveals a conserved and previously unknown regulator of desiccation in flowering plants

Water scarcity, resulting from climate change, poses a significant threat to ecosystems. Syntrichia ruralis, a dryland desiccation-tolerant moss, provides valuable insights into survival of water-limited conditions. We sequenced the genome of S. ruralis, conducted transcriptomic analyses, and performed comparative genomic and transcriptomic analyses with existing genomes and transcriptomes, including with the close relative S. caninervis. We took a genetic approach to characterize the role of an S. ruralis transcription factor, identified in transcriptomic analyses, in Arabidopsis thaliana. The genome was assembled into 12 chromosomes encompassing 21 169 protein-coding genes. Comparative analysis revealed copy number and transcript abundance differences in known desiccation-associated gene families, and highlighted genome-level variation among species that may reflect adaptation to different habitats. A significant number of abscisic acid (ABA)-responsive genes were found to be negatively regulated by a MYB transcription factor (MYB55) that was upstream of the S. ruralis ortholog of ABA-insensitive 3 (ABI3). We determined that this conserved MYB transcription factor, uncharacterized in Arabidopsis, acts as a negative regulator of an ABA-dependent stress response in Arabidopsis. The new genomic resources from this emerging model moss offer novel insights into how plants regulate their responses to water deprivation.

Predicting abiotic stress-responsive miRNA in plants based on multi-source features fusion and graph neural network

BACKGROUND

More and more studies show that miRNA plays a crucial role in plants' response to different abiotic stresses. However, traditional experimental methods are often expensive and inefficient, so it is important to develop efficient and economical computational methods. Although researchers have developed machine learning-based method, the information of miRNAs and abiotic stresses has not been fully exploited. Therefore, we propose a novel approach based on graph neural networks for predicting potential miRNA-abiotic stress associations.

RESULTS

In this study, we fully considered the multi-source feature information from miRNAs and abiotic stresses, and calculated and integrated the similarity network of miRNA and abiotic stress from different feature perspectives using multiple similarity measures. Then, the above multi-source similarity network and association information between miRNAs and abiotic stresses are effectively fused through heterogeneous networks. Subsequently, the Restart Random Walk (RWR) algorithm is employed to extract global structural information from heterogeneous networks, providing feature vectors for miRNA and abiotic stress. After that, we utilized the graph autoencoder based on GIN (Graph Isomorphism Networks) to learn and reconstruct a miRNA-abiotic stress association matrix to obtain potential miRNA-abiotic stress associations. The experimental results show that our model is superior to all known methods in predicting potential miRNA-abiotic stress associations, and the AUPR and AUC metrics of our model achieve 98.24% and 97.43%, respectively, under five-fold cross-validation.

CONCLUSIONS

The robustness and effectiveness of our proposed model position it as a valuable approach for advancing the field of miRNA-abiotic stress association prediction.

Sonographic features of Lemmel's syndrome: Differential diagnosis from stones in the lower portion of the common bile duct

BACKGROUND AND STUDY AIMS

Periampullary diverticula (PAD), a location-specific type of duodenal diverticula, can cause serious complications. PAD is difficult to differentially diagnose, mainly due to its nonspecific symptoms. This study aimed to identify sonographic features of PAD and to evaluate their value in the differential diagnosis of PAD from stones in the lower common bile duct (CBD).

PATIENTS AND METHODS

A total of 30 patients with PAD and 60 patients with lower CBD stones were retrospectively enrolled, and sonographic features were analyzed. Measurements of sonographic features included echo shaped, posterior echo changes, location and relation to surrounding organs, and status of intrahepatic and extrahepatic bile duct dilation, and their diagnostic performance was assessed.

RESULTS

Characteristic sonographic features of PAD were identified, including strong echoes (28/30, 93.3 %), strip shape (28/30, 93.3 %), multiple reflections in the posterior echo (27/30, 90.0 %), and location outside the CBD or near the biliary wall in connection with the duodenum (27/30, 90.0 %). Inter-observer agreement was good (Kappa values = 0.69-0.82). Comparative analysis of sonographic features revealed significant differences in echo shape, posterior echo changes (multiple reflections and acoustic shadowing), location and relation to surrounding organs, and intrahepatic and extrahepatic bile duct dilatation status between the dilatation status of the two groups. In particular, these characteristics achieved a sensitivity of 100 % and a specificity of 98 % for the differential diagnosis of PAD and lower CBD stones.

CONCLUSIONS

This study identified characteristic sonographic features of PAD, which could be used as potential diagnostic indicators to distinguish PAD from lower CBD stones.

Determination of the Σ^{+} Timelike Electromagnetic Form Factors

Based on data samples collected with the BESIII detector at the BEPCII collider, the process e^{+}e^{-}→Σ^{+}Σ[over ¯]^{-} is studied at center-of-mass energies sqrt[s]=2.3960, 2.6454, and 2.9000 GeV. Using a fully differential angular description of the final state particles, both the relative magnitude and phase information of the Σ^{+} electromagnetic form factors in the timelike region are extracted. The relative phase between the electric and magnetic form factors is determined to be sinΔΦ=-0.67±0.29(stat)±0.18(syst) at sqrt[s]=2.3960  GeV, ΔΦ=55°±19°(stat)±14°(syst) at sqrt[s]=2.6454  GeV, and 78°±22°(stat)±9°(syst) at sqrt[s]=2.9000  GeV. For the first time, the phase of the hyperon electromagnetic form factors is explored in a wide range of four-momentum transfer. The evolution of the phase along with four-momentum transfer is an important input for understanding its asymptotic behavior and the dynamics of baryons.

Relationship between observation time and detection rate of focal lesions in Esophagogastroduodenoscopy: a single-center, retrospective study

BACKGROUND

Current studies have shown that longer observation time can improve neoplastic detection rate. This study aimed to clarify whether endoscopists with longer observation times can detect more focal lesions.

METHODS

Based on the mean examination time for Esophagogastroduodenoscopy (EGD) without biopsy, endoscopists were divided into fast and slow groups, and the detection rate of focal lesions was compared between the two groups. Univariate analysis, multivariate analysis and restricted cubic spline were used to explore the factors of focal lesion detection rate.

RESULTS

Mean examination time of EGD without biopsy was 4.5 min. The cut-off times used were 5 min. 17 endoscopists were classified into the fast (4.7 ± 3.6 min), and 16 into the slow (7.11 ± 4.6 min) groups. Compared with fast endoscopists, slow endoscopists had a higher detection rate of focal lesions (47.2% vs. 51.4%, P < 0.001), especially in the detection of gastric lesions (29.7% vs. 35.9%, P < 0.001). In univariate and multivariate analyses, observation time, patient age and gender, expert, biopsy rate, and number of images were factors in FDR. There is a nonlinear relationship between observation time and FDR.

CONCLUSION

Longer examination time improves the detection rate of focal lesions. Observation time is an important quality indicator of the EGD examination.

Sasanquasaponin from Camellia oleifera Abel Exerts an Anti-Inflammatory Effect in RAW 264.7 Cells via Inhibition of the NF-κB/MAPK Signaling Pathways

Sasanquasaponin (SQS), a secondary metabolite that is derived from Camellia seeds, reportedly possesses notable biological properties. However, the anti-inflammatory effects of SQS and its underlying mechanisms remain poorly explored. Herein, we aimed to investigate the anti-inflammatory properties of SQS against lipopolysaccharide (LPS)-induced inflammatory responses in RAW264.7 cells, focusing on the nuclear factor-κB (NF-κB) and MAPK signaling pathways. SQS was isolated using a deep eutectic solvent and D101 macroporous adsorption resin and analyzed using high-performance liquid chromatography. The viability of LPS-stimulated RAW264.7 was assessed using the CCK-8 assay. The presence of reactive oxygen species (ROS) was evaluated using 2',7'-dichlorofluorescein-diacetate. The expression levels of inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (COX-2), tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6) were detected using reverse transcription-quantitative PCR and ELISA. Western blot was performed to analyze the protein expression of LPS-induced RAW264.7 cells. Herein, SQS exhibited anti-inflammatory activity: 30 μg/mL of SQS significantly reduced ROS generation, inhibited the LPS-induced expression of iNOS and COX-2, and attenuated the production of pro-inflammatory cytokines IL-1β, IL-6, and TNF-α. The anti-inflammatory activity was potentially mediated by inhibiting the phosphorylation of IκBα and p65 in the NF-κB signaling pathway and the phosphorylation of ERK and JNK in the MAPK signaling pathway. Accordingly, SQS could inhibit inflammation in LPS-induced RAW264.7 cells by suppressing the NF-κB and MAPK signaling pathways. This study demonstrated the potential application of SQS as an anti-inflammatory agent.

Comparison of Prompt Engineering and Fine-Tuning Strategies in Large Language Models in the Classification of Clinical Notes

The emerging large language models (LLMs) are actively evaluated in various fields including healthcare. Most studies have focused on established benchmarks and standard parameters; however, the variation and impact of prompt engineering and fine-tuning strategies have not been fully explored. This study benchmarks GPT-3.5 Turbo, GPT-4, and Llama-7B against BERT models and medical fellows' annotations in identifying patients with metastatic cancer from discharge summaries. Results revealed that clear, concise prompts incorporating reasoning steps significantly enhanced performance. GPT-4 exhibited superior performance among all models. Notably, one-shot learning and fine-tuning provided no incremental benefit. The model's accuracy sustained even when keywords for metastatic cancer were removed or when half of the input tokens were randomly discarded. These findings underscore GPT-4's potential to substitute specialized models, such as PubMedBERT, through strategic prompt engineering, and suggest opportunities to improve open-source models, which are better suited to use in clinical settings.

Toripalimab plus axitinib versus sunitinib as first-line treatment for advanced renal cell carcinoma: RENOTORCH, a randomized, open-label, phase III study

BACKGROUND

Immune checkpoint inhibitors in combination with tyrosine kinase inhibitors are standard treatments for advanced clear cell renal cell carcinoma (RCC). This phase III RENOTORCH study compared the efficacy and safety of toripalimab plus axitinib versus sunitinib for the first-line treatment of patients with intermediate-/poor-risk advanced RCC.

PATIENTS AND METHODS

Patients with intermediate-/poor-risk unresectable or metastatic RCC were randomized in a ratio of 1 : 1 to receive toripalimab (240 mg intravenously once every 3 weeks) plus axitinib (5 mg orally twice daily) or sunitinib [50 mg orally once daily for 4 weeks (6-week cycle) or 2 weeks (3-week cycle)]. The primary endpoint was progression-free survival (PFS) assessed by an independent review committee (IRC). The secondary endpoints were investigator-assessed PFS, overall response rate (ORR), overall survival (OS), and safety.

RESULTS

A total of 421 patients were randomized to receive toripalimab plus axitinib (n = 210) or sunitinib (n = 211). With a median follow-up of 14.6 months, toripalimab plus axitinib significantly reduced the risk of disease progression or death by 35% compared with sunitinib as assessed by an IRC [hazard ratio (HR) 0.65, 95% confidence interval (CI) 0.49-0.86; P = 0.0028]. The median PFS was 18.0 months in the toripalimab-axitinib group, whereas it was 9.8 months in the sunitinib group. The IRC-assessed ORR was significantly higher in the toripalimab-axitinib group compared with the sunitinib group (56.7% versus 30.8%; P < 0.0001). An OS trend favoring toripalimab plus axitinib was also observed (HR 0.61, 95% CI 0.40-0.92). Treatment-related grade ≥3 adverse events occurred in 61.5% of patients in the toripalimab-axitinib group and 58.6% of patients in the sunitinib group.

CONCLUSION

In patients with previously untreated intermediate-/poor-risk advanced RCC, toripalimab plus axitinib provided significantly longer PFS and higher ORR than sunitinib and had a manageable safety profile TRIAL REGISTRATION: ClinicalTrials.gov NCT04394975.

Mechanism of Cr(VI) bioreduction by Clostridium sp. LQ25 under Fe(III) reducing conditions

The Cr(VI) bioreduction has attracted widespread attention in the field of Cr(VI) pollution remediation due to its environmental friendliness. Further in-depth research on the reduction mechanisms is necessary to enhance the efficiency of Cr(VI) bioreduction. However, the limited research on Cr(VI) bioreduction mechanisms remains a bottleneck for the practical application of Cr(VI) reduction. In this study, The Cr(VI) reduction of strain LQ25 was significantly improved when Fe(III) was used as an electron acceptor, which increased by 1.6-fold maximum within the set Cr(VI) concentration range. Based on this, the electron transfer process of Cr(VI) reduction was analyzed using strain LQ25. Based on genomic data, flavin proteins were found to interact closely with electron transfer-related proteins using protein-protein interaction (PPi) analysis. Transcriptome analysis revealed that flavin synthesis genes (ribE, ribBA, and ribH) and electron transfer flavoprotein genes (fixA, etfA, fixB, and etfB) were significantly upregulated when Fe(III) was used as the electron acceptor. These results indicate that the fermentative dissimilatory Fe(III)-reducing bacterial strain LQ25 mainly uses flavin as an electron shuttle for electron transfer, which differs from the common use of cytochrome c in respiratory bacteria. These findings on the mechanism of Cr(VI) bioreduction provide technical support for improving the efficiency of Cr(VI) reduction which promote the practical application of Cr(VI) bioreduction in the field of Cr(VI) pollution remediation.