A spatial-potential resolved bipolar electrode electrochemiluminescence biosensor based on polarity conversion for dual-mode detection of miRNA-122 and CEA

In this work, a spatial-potential resolved bipolar electrode electrochemiluminescence (BPE-ECL) biosensor based on polarity conversion strategy and CuHCF electrocatalyst was constructed for dual-mode detection of miRNA-122 and carcinoembryonic antigen (CEA). ECL technology was firstly used to systematically study the polarity conversion of BPE. It was found that changing the polarity of the driving voltage would cause the polarity change of BPE, and led to the change of the luminescent position of Ru(bpy)32+. As a "proof-of-concept application", we developed a shielded dual-channel BPE-ECL biosensor for dual-mode detection of miRNA-122 and CEA. In order to further improve the detection sensitivity, a non-precious metal electrocatalyst CuHCF with outstanding electrocatalytic reduction activity of H2O2 was firstly introduced to the BPE-ECL biosensor for signal amplification, which could generate high faradaic current under the excitation of negative potential. Based on the charge neutrality principle of BPE, the enhancement of the faradaic current resulted in the ECL signal amplification of Ru(bpy)32+. The targets in the sensing grooves caused the introduction or fall off of CuHCF, which led to the ECL signal change of Ru(bpy)32+ in the signal grooves, and realized the dual-mode detection of miRNA-122 and CEA. This work provided a deeper understanding of the polarity change of BPE. Furthermore, the introduction of non-precious metal electrocatalyst had broadened the application range of BPE-ECL sensors.

A triple read-out visible biosensing platform based on multifunctional nanozyme and bipolar electrode for multi-mode detection and imaging of CEA

In this paper, a proposal of closed bipolar electrode (BPE) and nanozyme based multi-mode biosensing platform is first presented. As a novel integrated chip, multi-mode-BPE (MMBPE) combines enzyme-linked immunoassay (ELISA), electrochemiluminescence (ECL), ECL imaging and light emitting diode (LED) imaging, enabling highly sensitive triple read-out visible detection of cancer embryonic antigen (CEA). The ECL probe Ab2@Au@Co3O4/CoFe2O4 hollow nanocubes (HNCs) with excellent peroxidase (POD) activity is introduced into the BPE cathode through immune adsorption. The Au@Co3O4/CoFe2O4 HNCs can increase the rate of hydrogen peroxide oxidation of TMB, thus promoting the reaction, and can be used for ELISA detection of CEA at different concentrations. The modification of the BPE sensing interface and reporting interface involved the introduction of the luminescent reagent Ru(bpy)32+ to the BPE anode. The decomposition rate of H2O2 increased under the catalytic action of Au@Co3O4/CoFe2O4 HNCs nanozyme, leading to an accelerated electron transfer rate in the MMBPE system and an enhanced ECL signal from Ru(bpy)32+. The LED imaging technology further provides a convenient and visible approach for CEA imaging in which no additional chemicals are needed. The integration of nanoenzymes as the catalytic core in MMBPE system provides impetus, while the combination of nanozymes with BPE expands the application of nanoenzymes in the field of biological analysis. The integration of intelligent chips with multiple modes of detection shows portable, miniaturized, and integrated excellent properties which meets the requirements of modern detection devices and thus offers a flexible approach for determination of nucleic acids, proteins, and cells.

Photoelectrochemical sensor for the detection of Escherichia coli O157:H7 based on TPA-NO2 and dual-functional polythiophene films

The detection of Escherichia coli (E. coli) is of great significance for the environment and human health. Herein, a photoelectrochemical (PEC) detection strategy based on molecularly imprinted polymers (MIPs) was proposed for the sensitive detection of E. coli. 4,4',4″-Trinitrotriphenylamine (TPA-NO2) was prepared using a simple nitration reaction. Subsequently, MIP films were polymerized on the surface of TPA-NO2 using 1,3-dihydrothieno[3,2-d]pyrimidine-2,4-dione as the functional monomer with the dual functions of specific recognition and sensitization. The linear range was 10-108 CFU/mL and the limit of detection was 10 CFU/mL. It showed favorable recoveries in real sample tests of milk, orange juice and tomato. Additionally, the ability of functional monomers to bind excellently with E. coli was verified using molecular docking techniques. This research provided broader possibilities for constructing MIPs-PEC sensors and analyzing the interaction mechanism between E. coli and functional monomers.

Synergetic surface enhancement of quantum dots-based electrochemiluminescence with photonic crystal light scattering and metal surface plasmon resonance for sensitive bioanalysis

Noble metal nanostructures and photonic crystals (PhCs) have been widely investigated as substrates for constructing surface enhanced electrochemiluminescence (SE-ECL) biosensors. However, their applications are hindered by the limited enhancement intensity of surface plasmon resonance (SPR) and an incomplete mechanism for the photonic enhancement effect. Hence, developing a novel SE-ECL strategy with better signal enhanced capability and enriching our understanding of the intrinsic mechanisms for efficient bioanalysis is extremely urgent. Here, a synergistic SE-ECL strategy was developed for the sensitive determination of prostate specific antigen (PSA) protein. The randomly arranged polystyrene (r-PS) spheres and PS PhC arrays were applied to enhance the ECL emission of cadmium sulfide quantum dots (CdS QDs) and the results suggested that the PhC arrays displayed superior intensity (0.22) than the r-PS interface (0.10). Au nanoparticles (NPs) were introduced onto the two kinds of surfaces and further boosted the ECL intensity. According to the ECL measurements, Au NPs modified at the r-PS surface exhibited only a slight increase (0.13), while the PhC arrays showed approximately 5-fold enhancement (0.92), benefiting from the synergistic enhancement. The finite-difference time-domain (FDTD) simulation indicated that the ECL enhancement was ascribed to the coupled electromagnetic (EM) field at the surfaces of PS PhCs and Au NPs. The SE-ECL could achieve a detection range from 1 pg/mL to 1 μg/mL with a detection limit of 0.41 pg/mL (S/N = 3). This study provides the first combination of PhC arrays and metal surface plasmon nanostructure for the synergetic enhancement of SE-ECL systems. It opens a new avenue for the rational design of advanced ECL biosensors and shows great perspective for clinical diagnosis.

Aberrant LETM1 elevation dysregulates mitochondrial functions and energy metabolism and promotes lung metastasis in osteosarcoma

Osteosarcoma is a differentiation-deficient disease, and despite the unique advantages and great potential of differentiation therapy, there are only a few known differentiation inducers, and little research has been done on their targets. Cell differentiation is associated with an increase in mitochondrial content and activity. The metabolism of some tumor cells is characterized by impaired oxidative phosphorylation, as well as up-regulation of aerobic glycolysis and pentose phosphate pathways. Leucine-containing zipper and EF-hand transmembrane protein 1 (LETM1) is involved in the maintenance of mitochondrial morphology and is closely associated with tumorigenesis and progression, as well as cancer cell stemness. We found that MG63 and 143B osteosarcoma cells overexpress LETM1 and exhibit abnormalities in mitochondrial structure and function. Knockdown of LETM1 partially restored the mitochondrial structure and function, inhibited the pentose phosphate pathway, promoted oxidative phosphorylation, and led to osteogenic differentiation. It also inhibited spheroid cell formation, proliferation, migration, and invasion in an in vitro model. When LETM1 was knocked down in vivo, there was reduced tumor formation and lung metastasis. These data suggest that mitochondria are aberrant in LETM1-overexpressing osteosarcoma cells, and knockdown of LETM1 partially restores the mitochondrial structure and function, inhibits the pentose phosphate pathway, promotes oxidative phosphorylation, and increases osteogenic differentiation, thereby reducing malignant biological behavior of the cells.

Ultrasensitive electrochemiluminescence biosensor based on dual quenching effects of silver nanoclusters and multiple cycling amplification for detection of ATP

In this work, an electrochemiluminescence (ECL) biosensor based on dual ECL quenching effects of silver nanoclusters (Ag NCs) and multiple cycling amplification was designed to achieve ultrasensitive detection of ATP. The specific recognition of target ATP to aptamer initiated multiple cycling amplification, and a small amount of target was converted into a large number of DNA product chains (S1) by amplification. After S1 opened hairpin DNA 2 (HP2), Ag NCs approached the surface of CdS quantum dots (QDs) modified-electrode by complementary DNA, resulting in a significant decrease of ECL intensity from CdS QDs. The quenching principle is as follows. Firstly, the absorption spectrum of Ag NCs overlaps well with the ECL emission spectrum of CdS QDs, leading to effective ECL resonance energy transfer (ECL-RET); Secondly, Ag NCs could catalyze electrochemical reduction of K2S2O8, leading to consumption of ECL co-reactant and reducing ECL of QDs. The double-ECL quenching achieved ultrasensitive biosensing detection of ATP with a wide range from 1 aM to 1 pM. This present work reported new principle of double-quenching QDs ECL by Ag NCs, and developed a novel ECL biosensor by combining with multiple cycle amplification technique, which has great contribution to the development of QDs ECL and biosensing applications.

The glucocorticoid receptor in skeletal health and disease: insights from targeted knockout mice

Glucocorticoids are steroid hormones, secreted by the adrenals to regulate a range of metabolic, immunologic, and homeostatic functions. Due to their potent anti-inflammatory effects, synthetic glucocorticoids are widely used to treat inflammatory disorders. However, their use especially at high doses and over the long-term is associated with several unwanted side effects that compromises their intended use (e.g. glucocorticoid-induced osteoporosis and/or diabetes, myopathy, and skin atrophy). Both endogenous and synthetic glucocorticoids exert their effects through the glucocorticoid receptor, a transcription factor present in nearly all nucleated cells. Glucocorticoid receptor knockout mouse models have proved to be valuable tools in understanding how glucocorticoids contribute to skeletal health and disease. These models, described in this review, have helped to establish that the effects of glucocorticoids on the skeleton are multifaceted, cell specific and concentration dependent. Intriguingly, while endogenous glucocorticoids are essential for bone formation, high-dose exogenous glucocorticoids may induce bone loss. Additionally, the actions of endogenous glucocorticoids vary greatly depending on the disease microenvironment. For example, endogenous glucocorticoids have predominately beneficial anti-inflammatory effects in rheumatoid arthritis, but detrimental actions in osteoarthritis by driving cartilage loss and abnormal bone formation. Studies in tissue-specific knockout models provide important insights that will aid the development of new glucocorticoid therapeutics that can specifically target certain cell types to minimise unwanted effects from current glucocorticoid therapy.

MACTFusion: Lightweight Cross Transformer for Adaptive Multimodal Medical Image Fusion

Multimodal medical image fusion aims to integrate complementary information from different modalities of medical images. Deep learning methods, especially recent vision Transformers, have effectively improved image fusion performance. However, there are limitations for Transformers in image fusion, such as lacks of local feature extraction and cross-modal feature interaction, resulting in insufficient multimodal feature extraction and integration. In addition, the computational cost of Transformers is higher. To address these challenges, in this work, we develop an adaptive cross-modal fusion strategy for unsupervised multimodal medical image fusion. Specifically, we propose a novel lightweight cross Transformer based on cross multi-axis attention mechanism. It includes cross-window attention and cross-grid attention to mine and integrate both local and global interactions of multimodal features. The cross Transformer is further guided by a spatial adaptation fusion module, which allows the model to focus on the most relevant information. Moreover, we design a special feature extraction module that combines multiple gradient residual dense convolutional and Transformer layers to obtain local features from coarse to fine and capture global features. The proposed strategy significantly boosts the fusion performance while minimizing computational costs. Extensive experiments, including clinical brain tumor image fusion, have shown that our model can achieve clearer texture details and better visual quality than other state-of-the-art fusion methods.

Fish Arginase constrains Excessive Production of Nitric Oxide and Limits Mitochondrial Damage during Aeromonas hydrophila infection

Bacteria-enhanced inducible nitric oxide synthase (iNOS) overproduces nitric oxide (NO) leading to mitochondrial and cellular damage. In mammals, arginase (ARG), the enzyme consuming the same substrate L-arginine with iNOS, was believed to inhibit iNOS activity by competing the substrate. But in fish, this conception has been widely challenged. In this study, the gene expression using real-time quantitative PCR (RT-qPCR) technology showed that when stimulated by Aeromonas hydrophila (A. hydrophila), grass carp (gc) iNOS was up-regulated in head kidney monocytes/macrophages (M0/MФ), and its changes were not detected in the whole tissue of liver or spleen, showing a high degree of cell-specific expression pattern. At the same time, gcARG2 had a high basal expression in tissues and was up-regulated by A. hydrophila stimulation. Next, phthalaldehyde-primaquine reaction was first used in the determination of intracellular urea in fish cells. It was found that the induced gcARG2 led to an increase in the intracellular urea content. Moreover, urea and NO production in M0/MФ were increased in a substrate dose-dependent manner from 30 and 100 μM of L-arginine and reached the highest yield at 300 and 3000 μM of L-arginine, respectively. Furthermore, head kidney M0/MФ was cultured in RPMI1640 medium containing physiological concentration (500 μM) of L-arginine to evaluate the effect of ARG. Under A. hydrophila stimulation, treatment with the arginase inhibitor S-(2-boronoethyl)-l-cysteine (BEC) showed that inhibition of arginase could further enhance the NO production stimulated by A. hydrophila. This in turn led to a cumulation in peroxynitrite (ONOO-) content and an injure of the mitochondrial membrane potential. Our study showed for the first time that fish ARG in head kidney M0/MФ can limit excessive production of NO and harmful products by iNOS to maintain mitochondrial and cellular homeostasis.

Integration of 16 S rRNA gene sequencing, metabonomics and metagenome analysis to investigate the mechanism of Sparganium stoloniferum-Curcuma phaeocaulis in treating of endometriosis in rats

BACKGROUND

Endometriosis is a gynecological disease that causes severe chronic pelvic pain and infertility in women. The therapeutic efficacy of the traditional herbal combination of Sparganium stoloniferum-Curcuma phaeocaulis (Sangleng-Ezhu, SL-EZ) in the treatment of endometriosis has been established. However, the precise mechanism by which this treatment exerts its effects remains elusive.

METHODS

To gain further insights, UPLC-MS/MS was employed to identify the primary chemical constituents of SL-EZ in serum. Additionally, network pharmacology was utilized to analyze the active ingredients and their corresponding targets. Furthermore, the impact of SL-EZ on ectopic endometrial growth in endometrial implants was assessed using a rat model. The therapeutic mechanism of SL-EZ in rats with endometriosis was further investigated through the application of 16 S rRNA gene sequencing, metagenomic sequencing, and metabolomics.

RESULTS

The primary compounds in serum were zederone, p-coumaric acid, dehydrocostus lactone, curdione, curcumol. The growth of ectopic lesions in a rat model was effectively inhibited by SL-EZ. In comparison to the control group, the endometriotic rats exhibited a decrease in α-diversity of the gut microbiota, an increase in the Firmicutes/Bacteroidetes ratio, and a reduction in the abundance of Ruminococcaceae. Following SL-EZ intervention, the potential probiotic strains Lactobacillus gasseri and Lactobacillus johnsonii were able to restore the intestinal microenvironment at the species level. The altered metabolites were significantly correlated with Verrucomicrobia, Proteobacteria, and Bacteroidetes. The metabolomic analysis demonstrated significant alterations in intestinal metabolites. And SL-EZ intervention also exerted regulatory effects on various metabolic pathways in gut microbiota, including aminoacyl-tRNA biosynthesis, monobactam biosynthesis, cyanoamino acid metabolism, glycine, serine and threonine metabolism, plant secondary metabolite biosynthesis, and amino acid biosynthesis.

CONCLUSION

The identification of novel treatment formulations for endometriosis was achieved through the utilization of network pharmacology and gut microbiota analyses. Our findings revealed simultaneous alterations in the microbiota within the rat model of endometriosis. The therapeutic efficacy of SL-EZ in treating endometriosis is attributed to its ability to restore the gut microbiota and regulate metabolism. This investigation offers valuable insights into the therapeutic mechanisms of traditional Chinese medicine (TCM) for endometriosis.

Tumor microenvironment-activated theranostic nanozymes for trimodal imaging-guided combined therapy

Synergistic therapy is expected to be a promising strategy for highly effective cancer treatment. However, the rational design of a simple and multifunctional nanoplatform still remains a grand challenge. Considering the nature of weak acidic, hypoxic, and H2O2 abundant tumor microenvironment, we constructed an indocyanine green (ICG) modified platinum nanoclusters (Pt NCs) decorated gold nanobipyramids (Au NBPs) to form the multifunctional nanocomposites (Au NBPs@Pt NCs-ICG) for multimodal imaging mediated phototherapy and chemodynamic cancer therapy. The photosensitizer ICG was covalently linked to Au NBPs@Pt NCs by bridging molecules of SH-PEG-NH2 for both photodynamic therapy (PDT) and fluorescence imaging. Besides, Au NBPs@Pt NCs-ICG nanocomposites exhibited catalase- and peroxidase-like activities to generate O2 and ·OH, which relieved the tumor hypoxia and upregulated antitumoral ROS level. Moreover, the combination of Au NBPs and ICG endowed the Au NBPs@Pt NCs-ICG with super photothermal conversion for effective photothermal imaging and therapy. In addition, the Au NBPs@Pt NCs-ICG nanoplatform displayed excellent X-ray computed tomography (CT) imaging ability due to the presence of high-Z elements (Au and Pt). Overall, our results demonstrated that Au NBPs@Pt NCs-ICG nanoplatform exhibited a multimodal imaging guided synergistic PTT/PDT/CDT therapeutic manners and held great potential as an efficient treatment for breast cancer.

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.

Microneedle Delivery Platform Integrated with Codelivery Nanoliposomes for Effective and Safe Androgenetic Alopecia Treatment

Although topical application of minoxidil is a widely used, FDA-approved therapy for androgenetic alopecia (AGA) treatment, it suffers from low bioavailability, the requirement for frequent long-term use, and side effects. With a similar structure as minoxidil, kopexil and kopyrrol are less toxic and have been commercialized, but show an inferior hair regeneration effect compared to minoxidil. Herein, we developed a hyaluronic acid (HA)-based dissolvable microneedles (MNs) delivery platform integrated with kopexil and kopyrrol coencapsulated nanoliposomes (KK-NLPs) to effectively and safely treat AGA. Facilitated by nanoliposomes and MNs, the encapsulated KK-NLPs performed efficient skin penetration and enhanced cellular internalization into human dermal papilla cells. Furthermore, within the target cells, the codelivered kopexil and kopyrrol show synergistic effects by orchestrating an upregulation in the expression of Ki67, β-catenin, vascular endothelial growth factor (VEGF), and CD31. These molecular responses collectively foster cell proliferation, migration, and antioxidative effects, thereby facilitating the expedited progression of hair follicles (HFs) into the anagen phase and promoting peripheral angiogenesis. Notably, the KK-NLPs-integrated MNs treatment group exhibits noteworthy enhanced hair regeneration in vivo, with identical or superior therapeutic effects at a much lower dosage than that of minoxidil. These results suggest the great potential of this kopexil and kopyrrol codelivery nanoliposomes-integrated MNs platform for AGA treatment in a safe and efficient way.

Metformin normalizes mitochondrial function to delay astrocyte senescence in a mouse model of Parkinson's disease through Mfn2-cGAS signaling

BACKGROUND

Senescent astrocytes play crucial roles in age-associated neurodegenerative diseases, including Parkinson's disease (PD). Metformin, a drug widely used for treating diabetes, exerts longevity effects and neuroprotective activities. However, its effect on astrocyte senescence in PD remains to be defined.

METHODS

Long culture-induced replicative senescence model and 1-methyl-4-phenylpyridinium/α-synuclein aggregate-induced premature senescence model, and a mouse model of PD were used to investigate the effect of metformin on astrocyte senescence in vivo and in vitro. Immunofluorescence staining and flow cytometric analyses were performed to evaluate the mitochondrial function. We stereotactically injected AAV carrying GFAP-promoter-cGAS-shRNA to mouse substantia nigra pars compacta regions to specifically reduce astrocytic cGAS expression to clarify the potential molecular mechanism by which metformin inhibited the astrocyte senescence in PD.

RESULTS

We showed that metformin inhibited the astrocyte senescence in vitro and in PD mice. Mechanistically, metformin normalized mitochondrial function to reduce mitochondrial DNA release through mitofusin 2 (Mfn2), leading to inactivation of cGAS-STING, which delayed astrocyte senescence and prevented neurodegeneration. Mfn2 overexpression in astrocytes reversed the inhibitory role of metformin in cGAS-STING activation and astrocyte senescence. More importantly, metformin ameliorated dopamine neuron injury and behavioral deficits in mice by reducing the accumulation of senescent astrocytes via inhibition of astrocytic cGAS activation. Deletion of astrocytic cGAS abolished the suppressive effects of metformin on astrocyte senescence and neurodegeneration.

CONCLUSIONS

This work reveals that metformin delays astrocyte senescence via inhibiting astrocytic Mfn2-cGAS activation and suggest that metformin is a promising therapeutic agent for age-associated neurodegenerative diseases.

Deciphering chemoresistance in osteosarcoma: Unveiling regulatory mechanisms and function through the lens of noncoding RNA

Osteosarcoma (OS) is a primary malignant bone tumor and is prevalent in children, adolescents, and elderly individuals. It has the characteristics of high invasion and metastasis. Neoadjuvant chemotherapy combined with surgical resection is the most commonly used treatment for OS. However, the efficacy of OS is considerably diminished by chemotherapy resistance. In recent years, noncoding RNAs (ncRNAs), including microRNAs, long noncoding RNAs, and circular RNAs, are hot topics in the field of chemotherapy resistance research. Several studies have demonstrated that ncRNAs are substantially associated with chemoresistance in OS. Thus, the present study overviews the abnormally expressed ncRNAs in OS and the molecular mechanisms involved in chemoresistance, with an emphasis on their function in promoting or inhibiting chemoresistance. ncRNAs are expected to become potential therapeutic targets for overcoming drug resistance and predictive biomarkers in OS, which are of great significance for enhancing the therapeutic effect and improving the prognosis.

Selective removal of Hg(II) by chitosan derivative covalently modified with double cross-linking agents abundant in N and S atoms

With rapid industrialization and urbanization, numerous wastewater contains elevated concentration of Hg(II), and its concentration must be reduced to the discharge limit, so as not to cause serious pollution to the environment. In this paper, a modified chitosan adsorbent material, AMT-DMTD-CS (CS = chitosan, AMT = 2-amino-5-mercapto-1,3,4-thiadiazole, DMTD = 1,3,4-thiadiazole-2,5-dithiol) was prepared. FT-IR, XPS, elemental analysis, and FE-SEM confirmed that AMT and DMTD were successfully grafted covalently onto CS, with BET analysis showing a specific surface area of 105.55 m2/g for AMT-DMTD-CS. Adsorption study suggests that the optimal pH environment for AMT-DMTD-CS to adsorb Hg(II) is 4.0, and the saturated uptake capacity reaches 687.17 mg/g at 318 K, even after eight regenerations, the removal is still maintained at 80.06 %. Moreover, the adsorption behavior is in perfect agreement with the pseudo-second order kinetic model and the Langmuir isotherm model. In addition, AMT-DMTD-CS shows quite favorable selectivity for Hg(II) in a variety of co-existing metal ions. According to the FT-IR and XPS analysis of AMT-DMTD-CS-Hg(II), the synergistic complexation of -OH, -NH2, -NH, CN, CS and -SH to Hg(II) is considered as the main reason that leading to the elevated adsorption capacity.

Ganoderic acids alleviate atherosclerosis by inhibiting macrophage M1 polarization via TLR4/MyD88/NF-κB signaling pathway

BACKGROUND AND AIMS

Atherosclerosis (AS) is a chronic inflammatory disease characterized by lipid infiltration and plaque formation in blood vessel walls. Ganoderic acids (GA), a class of major bioactive compounds isolated from the Chinese traditional medicine Ganoderma lucidum, have multiple pharmacological activities. This study aimed to determine the anti-atherosclerotic effect of GA and reveal the pharmacological mechanism.

METHODS

ApoE-/- mice were fed a high-cholesterol diet and treated with GA for 16 weeks to induce AS and identify the effect of GA. Network pharmacological analysis was performed to predict the anti-atherosclerotic mechanisms. An invitro cell model was used to explore the effect of GA on macrophage polarization and the possible mechanism involved in bone marrow dereived macrophages (BMDMs) and RAW264.7 cells stimulated with lipopolysaccharide or oxidized low-density lipoprotein.

RESULTS

It was found that GA at 5 and 25 mg/kg/d significantly inhibited the development of AS and increased plaque stability, as evidenced by decreased plaque in the aorta, reduced necrotic core size and increased collagen/lipid ratio in lesions. GA reduced the proportion of M1 macrophages in plaques, but had no effect on M2 macrophages. In vitro experiments showed that GA (1, 5, 25 μg/mL) significantly decreased the proportion of CD86+ macrophages and the mRNA levels of IL-6, IL-1β, and MCP-1 in macrophages. Experimental results showed that GA inhibited M1 macrophage polarization by regulating TLR4/MyD88/NF-κB signaling pathway.

CONCLUSIONS

This study demonstrated that GA play an important role in plaque stability and macrophage polarization. GA exert the anti-atherosclerotic effect partly by regulating TLR4/MyD88/NF-κB signaling pathways to inhibit M1 polarization of macrophages. Our study provides theoretical basis and experimental data for the pharmacological activity and mechanisms of GA against AS.

TROPHY-U-01, a phase II open-label study of sacituzumab govitecan in patients with metastatic urothelial carcinoma progressing after platinum-based chemotherapy and checkpoint inhibitors: updated safety and efficacy outcomes

BACKGROUND

Sacituzumab govitecan (SG) is a Trop-2-directed antibody-drug conjugate containing cytotoxic SN-38, the active metabolite of irinotecan. SG received accelerated US Food and Drug Administration approval for locally advanced (LA) or metastatic urothelial carcinoma (mUC) previously treated with platinum-based chemotherapy and a checkpoint inhibitor, based on cohort 1 of the TROPHY-U-01 study. Mutations in the uridine diphosphate glucuronosyltransferase 1A1 (UGT1A1) gene are associated with increased adverse events (AEs) with irinotecan-based therapies. Whether UGT1A1 status could impact SG toxicity and efficacy remains unclear.

PATIENTS AND METHODS

TROPHY-U-01 (NCT03547973) is a multicohort, open-label, phase II registrational study. Cohort 1 includes patients with LA or mUC who progressed after platinum- and checkpoint inhibitor-based therapies. SG was administered at 10 mg/kg intravenously on days 1 and 8 of 21-day cycles. The primary endpoint was objective response rate (ORR) per central review; secondary endpoints included progression-free survival, overall survival, and safety. Post hoc safety analyses were exploratory with descriptive statistics. Updated analyses include longer follow-up.

RESULTS

Cohort 1 included 113 patients. At a median follow-up of 10.5 months, ORR was 28% (95% CI 20.2% to 37.6%). Median progression-free survival and overall survival were 5.4 months (95% CI 3.5-6.9 months) and 10.9 months (95% CI 8.9-13.8 months), respectively. Occurrence of grade ≥3 treatment-related AEs and treatment-related discontinuation were consistent with prior reports. UGT1A1 status was wildtype (∗1|∗1) in 40%, heterozygous (∗1|∗28) in 42%, homozygous (∗28|∗28) in 12%, and missing in 6% of patients. In patients with ∗1|∗1, ∗1|∗28, and ∗28|∗28 genotypes, any grade treatment-related AEs occurred in 93%, 94%, and 100% of patients, respectively, and were managed similarly regardless of UGT1A1 status.

CONCLUSIONS

With longer follow-up, the ORR remains high in patients with heavily pretreated LA or mUC. Safety data were consistent with the known SG toxicity profile. AE incidence varied across UGT1A1 subgroups; however, discontinuation rates remained relatively low for all groups.

[Retracted] Long non‑coding RNA SNHG6 promotes tumorigenesis in melanoma cells via the microRNA‑101‑3p/RAP2B axis

[This retracts the article DOI: 10.3892/ol.2020.12186.].

Predictive value of persistent antibodies at 6 months for relapse in neuronal surface antibody-associated autoimmune encephalitis

BACKGROUND

For patients with neuronal surface antibody-associated autoimmune encephalitis (NSAE) whose clinical symptoms gradually improve, the recommended course of immunotherapy in China is about 6 months. We aim to explore the relationship between persistent antibody positivity when immunotherapy is discontinued at 6 months and subsequent relapse.

METHODS

Prospective inclusion of NSAE patients with clinical remission after 6-month immunotherapy. Their antibody titers and other clinical data were collected at onset and 6 months later. Based on the antibody test results at 6 months, patients were divided into an antibody-persistent group and an antibody-negative conversion group, and then the rate of relapse between the two groups were compared.

RESULTS

The study included 28 NSAE patients who were antibody-positive at diagnosis. After 6-month immunotherapy, there were 16 (57.1%) cases with persistent antibodies and 12 (42.9%) cases with antibody-negative conversion. In the acute phase of onset, seizures were more common in patients with persistent antibodies (87.5% vs. 50.0%, p = 0.044). During a mean follow-up period of 22 months, patients with persistent antibodies were more likely to experience relapse than those with antibody-negative conversion (37.5% vs. 0.0%, p = 0.024). There were no significant differences in antibody types, CSF findings, results of MRI and EEG, tumor combination, immunotherapy, and long-term outcome between the two groups (p > 0.05).

CONCLUSIONS

For patients with persistent antibodies when immunotherapy is discontinued at 6 months, persistent antibody positivity was associated with a higher relapse rate.

Functional identification of two HMGB1 paralogues provides insights into autophagic machinery in teleost

High mobility group box 1 (HMGB1) is a multifunctional regulator that plays different roles in various physiological and pathological processes including cell development, autophagy, inflammation, tumor metastasis, and cell death based on its cellular localization. Unlike mammalian HMGB1, two HMGB1 paralogues (HMGB1a and HMGB1b) have been found in fathead minnow and other fish species and its function as an inflammatory cytokine has been well investigated. However, the role of fish HMGB1 in autophagy regulation has not been well clarified. In the present study, we generated HMGB1 paralogues single (HMGB1a-/- and HMGB1b-/-) and double knockout (DKO) epithelioma papulosum cyprini (EPC) cells from fathead minnow by CRISPR/Cas9 system, and the knockout efficiency of these genes was verified at both gene and protein levels. In this context, the effects of HMGB1 gene knockout on the protein expression of microtubule-associated protein 1 light chain 3 II (LC3-II), an autophagy marker, were determined, showing that single knockout of two HMGB1 paralogues significantly decreased the expression of LC3-II, and these inhibitory effects were further amplified in HMGB1 DKO cells under both basal and rapamycin treatment conditions, indicating the role of two HMGB1 paralogues in fish autophagy. In agreement with this notion, overexpression of HMGB1a or HMGB1b with Flag-tag markedly upregulated LC3-II protein expression. Interestingly, overexpressing two paralogues distributed in both cytoplasm and nucleus. Finally, the role of HMGB1-mediated autophagy was further explored, finding that HMGB1 could interact with Beclin1, a key initiation factor of autophagy. Taken together, these findings highlighted the role of HMGB1 paralogues as the autophagy regulator and increased our understanding of autophagic machinery in teleost.

Lipin-1 deficiency deteriorates defect of fatty acid β-oxidation and lipid-related kidney damage in diabetic kidney disease

Diabetic lipo-toxicity is a fundamental pathophysiologic mechanism in DM and is now increasingly recognized a key determinant of DKD. Targeting lipid metabolic disorders is an important therapeutic strategy for the treatment of DM and its complications, including DKD. This study aimed to explore the molecular mechanism of lipid metabolic regulation in kidney, especially renal PTECs, and elucidate the role of lipid metabolic related molecule lipin-1 in diabetic lipid-related kidney damage. In this study, lipin-1-deficient db/db mouse model and STZ/HFD-induced T2DM mouse model were used to determine the effect of lipin-1 on DKD development. Then RPTCs and LPIN1 knockdown or overexpressed HK-2 cells induced by PA were used to investigate the mechanism. We found that the expression of lipin-1 increased early and then decreased in kidney during the progression of DKD. Glucose and lipid metabolic disorders and renal insufficiency were found in these 2 types of diabetic mouse models. Interestingly, lipin-1 deficiency might be a pathogenic driver of DKD-to-CKD transition, which could further accelerate the imbalance of renal lipid homeostasis, the dysfunction of mitochondrial and energy metabolism in PTECs. Mechanistically, lipin-1 deficiency resulted in aggravated PTECs injury to tubulointerstitial fibrosis in DKD by downregulating FAO via inhibiting PGC-1α/PPARα mediated Cpt1α/HNF4α signaling and upregulating SREBPs to promote fat synthesis. This study provided new insights into the role of lipin-1 as a regulator for maintaining lipid homeostasis in the kidney, especially PTECs, and its deficiency led to the progression of DKD.

A mixed blessing of influent leachate microbes in downstream biotreatment systems of a full-scale landfill leachate treatment plant

In landfill leachate treatment plants (LLTPs), the microbiome plays a pivotal role in the decomposition of organic compounds, reduction in nutrient levels, and elimination of toxins. However, the effects of microbes in landfill leachate influents on downstream treatment systems remain poorly understood. To address this knowledge gap, we collected 23 metagenomic and 12 metatranscriptomic samples from landfill leachate and activated sludge from various treatment units in a full-scale LLTP. We successfully recovered 1,152 non-redundant metagenome-assembled genomes (MAGs), encompassing a wide taxonomic range, including 48 phyla, 95 classes, 166 orders, 247 families, 238 genera, and 1,152 species. More diverse microbes were observed in the influent leachate than in the downstream biotreatment systems, among which, an unprecedented ∼30 % of microbes with transcriptional expression migrated from the influent to the biological treatment units. Network analysis revealed that 399 shared MAGs across the four units exhibited high node centrality and degree, thus supporting enhanced interactions and increased stability of microbial communities. Functional reconstruction and genome characterization of MAGs indicated that these shared MAGs possessed greater capabilities for carbon, nitrogen, sulfur, and arsenic metabolism compared to non-shared MAGs. We further identified a novel species of Zixibacteria in the leachate influent with discrete lineages from those in other environments that accounted for up to 17 % of the abundance of the shared microbial community and exhibited notable metabolic versatility. Meanwhile, we presented groundbreaking evidence of the involvement of Zixibacteria-encoded genes in the production of harmful gas emissions, such as N2O and H2S, at the transcriptional level, thus suggesting that influent microbes may pose safety risks to downstream treatment systems. In summary, this study revealed the complex impact of the influent microbiome on LLTP and emphasizes the need to consider these microbial characteristics when designing treatment technologies and strategies for landfill leachate management.

FANCD2 deficiency sensitizes SHH medulloblastoma to radiotherapy via ferroptosis

Radiotherapy is one of the standard therapeutic regimens for medulloblastoma (MB). Tumor cells utilize DNA damage repair (DDR) mechanisms to survive and develop resistance during radiotherapy. It has been found that targeting DDR sensitizes tumor cells to radiotherapy in several types of cancer, but whether and how DDR pathways are involved in the MB radiotherapy response remain to be determined. Single-cell RNA sequencing was carried out on 38 MB tissues, followed by expression enrichment assays. Fanconi anemia group D2 gene (FANCD2) expression was evaluated in MB samples and public MB databases. The function of FANCD2 in MB cells was examined using cell counting assays (CCK-8), clone formation, lactate dehydrogenase activity, and in mouse orthotopic models. The FANCD2-related signaling pathway was investigated using assays of peroxidation, a malondialdehyde assay, a reduced glutathione assay, and using FerroOrange to assess intracellular iron ions (Fe2+ ). Here, we report that FANCD2 was highly expressed in the malignant sonic hedgehog (SHH) MB subtype (SHH-MB). FANCD2 played an oncogenic role and predicted worse prognosis in SHH-MB patients. Moreover, FANCD2 knockdown markedly suppressed viability, mobility, and growth of SHH-MB cells and sensitized SHH-MB cells to irradiation. Mechanistically, FANCD2 deficiency led to an accumulation of Fe2+ due to increased divalent metal transporter 1 expression and impaired glutathione peroxidase 4 activity, which further activated ferroptosis and reduced proliferation of SHH-MB cells. Using an orthotopic mouse model, we observed that radiotherapy combined with silencing FANCD2 significantly inhibited the growth of SHH-MB cell-derived tumors in vivo. Our study revealed FANCD2 as a potential therapeutic target in SHH-MB and silencing FANCD2 could sensitize SHH-MB cells to radiotherapy via inducing ferroptosis. © 2024 The Pathological Society of Great Britain and Ireland.

Protraction of Mandibular Second Molar for Substitution of Adjacent Missing First Molar With a Mini-Implant-Anchored Albert Loop Appliance

Protraction of mandibular posterior teeth into edentulous regions is challenging in clinical practice. This case demonstrated a minor tooth movement of a mandibular second molar to substitute its adjacent missing first molar in a 15-year-old female. An efficient bodily movement of the mandibular second molar was achieved through a mini-implant-anchored protraction loop appliance. With this carefully designed biomechanical system, over 10-mm molar protraction was accomplished within 14 months without mesial or lingual tipping. The adjacent third molar erupted spontaneously during the protraction process and drafted mesially. Through brackets and segmented archwire after the protraction, the second and third molars were successfully protracted and good buccal interdigitation was achieved. The combination of the Albert protraction loop and mini-implant allows for more efficient protraction of the mandibular molars, avoiding mesial tipping and lingual rotation of the molars.

Supercritical CO2 mediated construction of aluminium waste recovered γ-Al2O3 impregnated Dracaena trifasciata biomass-derived carbon composite: A robust electrocatalyst for mutagenic pollutant detection

Inspired by the waste-to-wealth concept, we have recovered the gamma phase aluminium oxide nanoparticles (γ-Al2O3 NPs) from waste aluminium (Al) foils and fabricated a composite with Dracaena trifasciata biomass-derived activated carbon matrix (DT-AC) using supercritical carbon-di-oxide (SC-CO2) pathway. The prepared samples are characterized altogether by various micro- and spectroscopic analyses. Based on the results, the recovered γ-Al2O3 NPs are well impregnated in the DT-AC surface by the action of the microbubble effect from the SC-CO2. The higher D-band and ID/IG value of 1.07 in the Al2O3/DT-AC nanocomposite indicate increased defects and the amorphous nature of the carbon materials. The effect of scan rate (ν) demonstrated greater linearity in ν1/2 vs peak current in the electrochemical detection study of the mutagenic pollutant 4-(methylamino) phenol hemi sulfate, showing a quasi-reversible electron transfer process undergoing diffusion-controlled kinetics. Furthermore, the limit of detection is determined to be 3.2 nM L-1 with an extensive linear range, spanning from 0.05 to 618.25 µM/L. The incredible sensitivity of 2.117 μA μM-1 cm-2, along with excellent selectivity, repeatability, and stability, is observed. Further, the respectable recovery percentage of 98.61 % in the environmental water sample is perceived. The observed outcomes suggest that the prepared Al2O3/DT-AC composite performs as an excellent electrocatalyst material, and the processing techniques used are thought to be sustainable in nature.

Development and Validation of a Deep Learning and Radiomics Combined Model for Differentiating Complicated From Uncomplicated Acute Appendicitis

RATIONALE AND OBJECTIVES

This study aimed to develop and validate a deep learning and radiomics combined model for differentiating complicated from uncomplicated acute appendicitis (AA).

MATERIALS AND METHODS

This retrospective multicenter study included 1165 adult AA patients (training cohort, 700 patients; validation cohort, 465 patients) with available abdominal pelvic computed tomography (CT) images. The reference standard for complicated/uncomplicated AA was the surgery and pathology records. We developed our combined model with CatBoost based on the selected clinical characteristics, CT visual features, deep learning features, and radiomics features. We externally validated our combined model and compared its performance with that of the conventional combined model, the deep learning radiomics (DLR) model, and the radiologist's visual diagnosis using receiver operating characteristic (ROC) curve analysis.

RESULTS

In the training cohort, the area under the ROC curve (AUC) of our combined model in distinguishing complicated from uncomplicated AA was 0.816 (95% confidence interval [CI]: 0.785-0.844). In the validation cohort, our combined model showed robust performance across the data from three centers, with AUCs of 0.836 (95% CI: 0.785-0.879), 0.793 (95% CI: 0.695-0.872), and 0.723 (95% CI: 0.632-0.802). In the total validation cohort, our combined model (AUC = 0.799) performed better than the conventional combined model, DLR model, and radiologist's visual diagnosis (AUC = 0.723, 0.755, and 0.679, respectively; all P < 0.05). Decision curve analysis showed that our combined model provided greater net benefit in predicting complicated AA than the other three models.

CONCLUSION

Our combined model allows the accurate differentiation of complicated and uncomplicated AA.

A revisit of drugs and potential therapeutic targets against non-alcoholic fatty liver disease: learning from clinical trials

PURPOSE

Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease, with a worldwide prevalence of 25%. Although numerous clinical trials have been conducted over the last few decades, an effective treatment has not been approved yet. Extensive research has accumulated a large amount of data and experience; however, the vast number of clinical trials and new therapeutic targets for NAFLD make it impossible to keep abreast of the relevant information. Therefore, a systematic analysis of the existing trials is necessary.

METHODS

Here, we reviewed clinical trials on NAFLD registered in the mandated federal database, ClinicalTrials.gov, to generate a detailed overview of the trials related to drugs and therapeutic targets for NAFLD treatment. Following screening for pertinence to therapy, a total of 440 entries were identified that included active trials as well as those that have already been completed, suspended, terminated, or withdrawn.

RESULTS

We summarize and systematically analyze the state, drug development pipeline, and discovery of treatment targets for NAFLD. We consider possible factors that may affect clinical outcomes. Furthermore, we discussed these results to explore the mechanisms responsible for clinical outcomes.

CONCLUSION

We summarised the landscape of current clinical trials and suggested the directions for future NAFLD therapy to assist internal medicine specialists in treating the whole clinical spectrum of this highly prevalent liver disease.

Associations of sleep-related variables with reverse dipping patterns of blood pressure in α-synucleinopathies

INTRODUCTION

The reverse dipping blood pressure (BP) pattern is very common in α-synucleinopathies. We aimed to explore the associations of sleep-related variables with abnormal BP circadian rhythms in Parkinson's disease (PD) and multiple system atrophy (MSA).

METHODS

A total of 126 patients, 76 with PD and 50 with MSA, were included. All participants underwent ambulatory BP monitoring and full-night polysomnography (PSG). We analyzed abnormal dipping patterns and sleep-related parameters, including moderate to severe obstructive sleep apnea (OSA), rapid eye movement behavior disorder (RBD), average oxygen saturation (SaO2%), lowest SaO2%, duration of SaO2% <90%, and apnea-hypopnea index (AHI). Binary logistic regression was performed to explore the associations between paraclinical variables, sleep-related variables, and reverse dipping patterns.

RESULTS

Reverse dipping patterns were predominant in patients with PD (58.5 %) and MSA (68.0 %). Patients with MSA had higher AHI, RBD, and lower average SaO2% than those with PD. Taking both diseases together as a whole group of α-synucleinopathies, logistic regression analysis indicates the Hoehn-Yahr stage (odds ratio [OR] = 2.00 for reverse systolic and 2.34 for reverse diastolic dipping patterns), moderate to severe OSA (OR = 2.71 for reverse systolic and 2.53 for reverse diastolic dipping patterns), average SaO2% (OR = 1.35 for reverse systolic dipping patterns), and male sex (OR = 2.70 for reverse diastolic dipping patterns) were independently associated with reverse dipping patterns.

CONCLUSIONS

Reverse dipping patterns were common in patients with PD and MSA. Hoehn-Yahr stage, moderate to severe OSA, average SaO2%, and male sex were associated with reverse dipping patterns in α-synucleinopathy.

Metformin suppresses NFE2L1 pathway activation to inhibit gap junction beta protein expression in NSCLC

OBJECTIVE

Non-small-cell lung cancer (NSCLC) is a deadly form of cancer that exhibits extensive intercellular communication which contributed to chemoradiotherapy resistance. Recent evidence suggests that arrange of key proteins are involved in lung cancer progression, including gap junction proteins (GJPs).

METHODS AND RESULTS

In this study, we examined the expression patterns of GJPs in NSCLC, uncovering that both gap junction protein, beta 2 (GJB2) and gap junction protein, beta 2 (GJB3) are increased in LUAD and LUSC. We observed a correlation between the upregulation of GJB2, GJB3 in clinical samples and a worse prognosis in patients with NSCLC. By examining the mechanics, we additionally discovered that nuclear factor erythroid-2-related factor 1 (NFE2L1) had the capability to enhance the expression of connexin26 and connexin 31 in the NSCLC cell line A549. In addition, the use of metformin was discovered to cause significant downregulation of gap junction protein, betas (GJBs) by limiting the presence of NFE2L1 in the cytoplasm.

CONCLUSION

This emphasizes the potential of targeting GJBs as a viable treatment approach for NSCLC patients receiving metformin.

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

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

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

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

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Affiliation(s)

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

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

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

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

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

Rapid determination of glyphosate and glufosinate in human blood by probe electrospray ionization tandem mass spectrometry

In forensic science, glyphosate (GLYP) and glufosinate (GLUF), a class of non-selective broad-spectrum herbicides, have been frequently encountered in many fatal poisoning and suicide cases due to their widespread availability. Therefore, it is essential to develop an effective method for detecting these compounds. Some conventional methods, such as gas chromatography-mass spectrometry (GC-MS) or liquid chromatography-mass spectrometry (LC-MS), have been reported to detect these compounds. However, these methods are not ideal for their time-consuming and non-sensitive feature. Herein, probe electrospray ionization (PESI) tandem mass spectrometry (MS/MS), a fast and sensitive technique, was applied for the determination of GLYP and GLUF in human blood, which can obtain analytical results within 0.5 min without derivatization and chromatographic separation. After protein precipitation of blood samples, the supernatant was mixed with isopropanol and ultra-pure water (1:1 v/v). Then, 8 μL of the mixture was introduced into the plastic sample plate for PESI-MS/MS analysis. The limits of detection (LODs) of the method were 0.50 μg/mL and 0.25 μg/mL for two analytes, and the limits of quantitation (LOQs) were both 1.00 μg/mL, which are higher than the concentration of reported poisoning and fatal cases. In the linear range of 1-500 μg/mL, the regression coefficients (r2) for GLYP and GLUF were over 0.99. The matrix effects ranged from 94.8 % to 119.5 %, and the biases were below 4.3 %. The recoveries ranged between 84.8 % and 107.4 %, and the biases were below 7.6 %. Meanwhile, the method was effectively utilized to detect and quantify the blood, urine, and other samples. Consequently, the results suggest that PESI-MS/MS is a straightforward, fast, and sensitive method for detecting GLUF and GLYP in forensics. In the future, PESI-MS/MS will become an indispensable technique for polar substances in grassroots units of public security where rapid detection is essential.

LncRNA and mRNA expression characteristic and bioinformatic analysis in myocardium of diabetic cardiomyopathy mice

BACKGROUND

Diabetic cardiomyopathy (DCM) is becoming a very well-known clinical entity and leads to increased heart failure in diabetic patients. Long non-coding RNAs (LncRNAs) play an important role in the pathogenesis of DCM. In the present study, the expression profiles of lncRNAs and mRNAs were illuminated in myocardium from DCM mice, with purpose of exploring probable pathological processes of DCM involved by differentially expressed genes in order to provide a new direction for the future researches of DCM.

RESULTS

The results showed that a total of 93 differentially expressed lncRNA transcripts and 881 mRNA transcripts were aberrantly expressed in db/db mice compared with the controls. The top 6 differentially expressed lncRNAs like up-regulated Hmga1b, Gm8909, Gm50252 and down-regulated Msantd4, 4933413J09Rik, Gm41414 have not yet been reported in DCM. The lncRNAs-mRNAs co-expression network analysis showed that LncRNA 2610507I01Rik, 2310015A16Rik, Gm10503, A930015D03Rik and Gm48483 were the most relevant to differentially expressed mRNAs.

CONCLUSION

Our results showed that db/db DCM mice exist differentially expressed lncRNAs and mRNAs in hearts. These differentially expressed lncRNAs may be involved in the pathological process of cardiomyocyte apoptosis and fibrosis in DCM.

Deep learning-based 3D cerebrovascular segmentation workflow on bright and black blood sequences magnetic resonance angiography

BACKGROUND

Cerebrovascular diseases have emerged as significant threats to human life and health. Effectively segmenting brain blood vessels has become a crucial scientific challenge. We aimed to develop a fully automated deep learning workflow that achieves accurate 3D segmentation of cerebral blood vessels by incorporating classic convolutional neural networks (CNNs) and transformer models.

METHODS

We used a public cerebrovascular segmentation dataset (CSD) containing 45 volumes of 1.5 T time-of-flight magnetic resonance angiography images. We collected data from another private middle cerebral artery (MCA) with lenticulostriate artery (LSA) segmentation dataset (MLD), which encompassed 3.0 T three-dimensional T1-weighted sequences of volumetric isotropic turbo spin echo acquisition MRI images of 107 patients aged 62 ± 11 years (42 females). The workflow includes data analysis, preprocessing, augmentation, model training with validation, and postprocessing techniques. Brain vessels were segmented using the U-Net, V-Net, UNETR, and SwinUNETR models. The model performances were evaluated using the dice similarity coefficient (DSC), average surface distance (ASD), precision (PRE), sensitivity (SEN), and specificity (SPE).

RESULTS

During 4-fold cross-validation, SwinUNETR obtained the highest DSC in each fold. On the CSD test set, SwinUNETR achieved the best DSC (0.853), PRE (0.848), SEN (0.860), and SPE (0.9996), while V-Net achieved the best ASD (0.99). On the MLD test set, SwinUNETR demonstrated good MCA segmentation performance and had the best DSC, ASD, PRE, and SPE for segmenting the LSA.

CONCLUSIONS

The workflow demonstrated excellent performance on different sequences of MRI images for vessels of varying sizes. This method allows doctors to visualize cerebrovascular structures.

CRITICAL RELEVANCE STATEMENT

A deep learning-based 3D cerebrovascular segmentation workflow is feasible and promising for visualizing cerebrovascular structures and monitoring cerebral small vessels, such as lenticulostriate arteries.

KEY POINTS

• The proposed deep learning-based workflow performs well in cerebrovascular segmentation tasks. • Among comparison models, SwinUNETR achieved the best DSC, ASD, PRE, and SPE values in lenticulostriate artery segmentation. • The proposed workflow can be used for different MR sequences, such as bright and black blood imaging.

Sympathetic nerve-enteroendocrine L cell communication modulates GLP-1 release, brain glucose utilization, and cognitive function

Glucose homeostasis is controlled by brain-gut communications. Yet our understanding of the neuron-gut interface in the glucoregulatory system remains incomplete. Here, we find that sympathetic nerves elevate postprandial blood glucose but restrict brain glucose utilization by repressing the release of glucagon-like peptide-1 (GLP-1) from enteroendocrine L cells. Sympathetic nerves are in close apposition with the L cells. Importantly, sympathetic denervation or intestinal deletion of the adrenergic receptor α2 (Adra2a) augments postprandial GLP-1 secretion, leading to reduced blood glucose levels and increased brain glucose uptake. Conversely, sympathetic activation shows the opposite effects. At the cellular level, adrenergic signaling suppresses calcium flux to limit GLP-1 secretion upon sugar ingestion. Consequently, abrogation of adrenergic signal results in a significant improvement in learning and memory ability. Together, our results reveal a sympathetic nerve-enteroendocrine unit in constraining GLP-1 secretion, thus providing a therapeutic nexus of mobilizing endogenous GLP-1 for glucose management and cognitive improvement.

Identification of novel mammalian viruses in tree shrews ( Tupaia belangeri chinensis)

The Chinese tree shrew ( Tupaia belangeri chinensis), a member of the mammalian order Scandentia, exhibits considerable similarities with primates, including humans, in aspects of its nervous, immune, and metabolic systems. These similarities have established the tree shrew as a promising experimental model for biomedical research on cancer, infectious diseases, metabolic disorders, and mental health conditions. Herein, we used meta-transcriptomic sequencing to analyze plasma, as well as oral and anal swab samples, from 105 healthy asymptomatic tree shrews to identify the presence of potential zoonotic viruses. In total, eight mammalian viruses with complete genomes were identified, belonging to six viral families, including Flaviviridae, Hepeviridae, Parvovirinae, Picornaviridae, Sedoreoviridae, and Spinareoviridae. Notably, the presence of rotavirus was recorded in tree shrews for the first time. Three viruses - hepacivirus 1, parvovirus, and picornavirus - exhibited low genetic similarity (<70%) with previously reported viruses at the whole-genome scale, indicating novelty. Conversely, three other viruses - hepacivirus 2, hepatovirus A and hepevirus - exhibited high similarity (>94%) to known viral strains. Phylogenetic analyses also revealed that the rotavirus and mammalian orthoreovirus identified in this study may be novel reassortants. These findings provide insights into the diverse viral spectrum present in captive Chinese tree shrews, highlighting the necessity for further research into their potential for cross-species transmission.

Characterization and in vitro antibacterial activity of grass carp (Ctenopharyngodon idella) serum amyloid A

Serum amyloid A (SAA) predominantly synthesized by hepatocytes is a classical acute phase protein and has been extensively studied in mammals. However, the studies on the structure and properties of fish SAA are limited although SAA genes have been cloned and identified from various fishes. In the present study, a cDNA of grass carp (Ctenopharyngodon idella) SAA (gcSAA) was cloned and characterized, displaying a high homology with its counterparts in vertebrates. gcSAA mRNA was expressed with highest abundance in the liver and its levels were increased by a 24-hour infection of Aeromonas hydrophila (A. hydrophila) for more than 5 folds in the intestine, 15 folds in the spleen, 75 folds in the head kidney and 100 folds in the liver, implying that it is an acute phase protein in grass carp. Subsequently, recombinant gcSAA protein (rgcSAA) was prepared from a prokaryotic expression system after codon optimization of its coding sequence. The direct antibacterial activity assay and the plate count assay disclosed that gcSAA inhibited the growth and survival of A. hydrophila but not Edwardsiella piscicida (E. piscicida) which both are common bacterial pathogens in aquaculture. The propidium iodide (PI) uptake assay confirmed the bactericidal property of gcSAA, showing that it is able to enhance the uptake of PI in A. hydrophila but not E. piscicida. These findings revealed the molecular features of gcSAA and its roles in host defense against bacterial infection.

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.

Appropriate whole genome amplification and pathogenic loci detection can improve the accuracy of preimplantation genetic diagnosis for deletional α-thalassemia

Objective

To improve the accuracy of preimplantation genetic testing (PGT) in deletional α-thalassemia patients.

Design

Article.

Patients

fifty-two deletional α-thalassemia couples.

Interventions

Whole genome amplification (WGA), Next-generation sequencing (NGS) and PCR mutation loci detection.

Main outcome measures

WGA, Single nucleotide polymorphism (SNP) and PCR mutation loci detection results; Analysis of embryo chromosome copy number variation (CNV).

Results

Multiple Displacement Amplification (MDA) and Multiple Annealing and Looping-Based Amplification Cycles (MALBAC) methods for PGT for deletional α-thalassemia. Blastocyst biopsy samples (n = 253) were obtained from 52 deletional α-thalassemia couples. The results of the comparison of experimental data between groups MALBAC and MDA are as follows: (i) The average allele drop-out (ADO) rate, MALBAC vs. MDA = 2.27% ± 3.57% vs. 0.97% ± 1.4%, P=0.451); (ii) WGA success rate, MALBAC vs. MDA = 98.61% vs. 98.89%, P=0.851; (iii) SNP haplotype success rate, MALBAC vs. MDA = 94.44% vs. 96.68%, P=0.409; (iv) The result of SNP haplotype analysis is consistent with that of Gap-PCR/Sanger sequencing results, MALBAC vs. MDA = 36(36/72, 50%) vs. 151(151/181, 83.43%), P=0; (v) Valid SNP loci, MALBAC vs. MDA = 30 ± 9 vs. 34 ± 10, P=0.02; (vi) The mean CV values, MALBAC vs. MDA = 0.12 ± 0.263 vs. 0.09 ± 0.40, P=0.916; (vii) The average number of raw reads, MALBAC vs. MDA =3244259 ± 999124 vs. 3713146 ± 1028721, P=0; (viii) The coverage of genome (%), MALBAC vs. MDA = 5.02 ± 1.09 vs. 5.55 ± 1.49, P=0.008.

Conclusions

Our findings indicate that MDA is superior to MALBAC for PGT of deletional α-thalassemia. Furthermore, SNP haplotype analysis combined with PCR loci detection can improve the accuracy and detection rate of deletional α-thalassemia.

Measurement of the Centrality Dependence of the Dijet Yield in p+Pb Collisions at sqrt[s_{NN}]=8.16 TeV with the ATLAS Detector

ATLAS measured the centrality dependence of the dijet yield using 165  nb^{-1} of p+Pb data collected at sqrt[s_{NN}]=8.16  TeV in 2016. The event centrality, which reflects the p+Pb impact parameter, is characterized by the total transverse energy registered in the Pb-going side of the forward calorimeter. The central-to-peripheral ratio of the scaled dijet yields, R_{CP}, is evaluated, and the results are presented as a function of variables that reflect the kinematics of the initial hard parton scattering process. The R_{CP} shows a scaling with the Bjorken x of the parton originating from the proton, x_{p}, while no such trend is observed as a function of x_{Pb}. This analysis provides unique input to understanding the role of small proton spatial configurations in p+Pb collisions by covering parton momentum fractions from the valence region down to x_{p}∼10^{-3} and x_{Pb}∼4×10^{-4}.

Tetrahedral DNA loaded siCCR2 restrains M1 macrophage polarization to ameliorate pulmonary fibrosis in chemoradiation-induced murine model

Idiopathic pulmonary fibrosis (IPF) is a chronic lethal disease in the absence of demonstrated efficacy for preventing progression. Although macrophage-mediated alveolitis is determined to participate in myofibrotic transition during disease development, the paradigm of continuous macrophage polarization is still under-explored due to lack of proper animal models. Here, by integrating 2.5 U/kg intratracheal Bleomycin administration and 10 Gy thorax irradiation at day 7, we generated a murine model with continuous alveolitis-mediated fibrosis, which mimics most of the clinical features of our involved IPF patients. In combination with data from scRNA-seq of patients and a murine IPF model, a decisive role of CCL2/CCR2 axis in driving M1 macrophage polarization was revealed, and M1 macrophage was further confirmed to boost alveolitis in leading myofibroblast activation. Multiple sticky-end tetrahedral framework nucleic acids conjunct with quadruple ccr2-siRNA (FNA-siCCR2) was synthesized in targeting M1 macrophages. FNA-siCCR2 successfully blocked macrophage accumulation in pulmonary parenchyma of the IPF murine model, thus preventing myofibroblast activation and leading to the disease remitting. Overall, our studies lay the groundwork to develop a novel IPF murine model, reveal M1 macrophages as potential therapeutic targets, and establish new treatment strategy by using FNA-siCCR2, which are highly relevant to clinical scenarios and translational research in the field of IPF.

Correlation Between Cognitive Impairment and Lenticulostriate Arteries: A Clinical and Radiomics Analysis

Lenticulostriate arteries (LSA) are potentially valuable for studying vascular cognitive impairment. This study aims to investigate correlations between cognitive impairment and LSA through clinical and radiomics features analysis. We retrospectively included 102 patients (mean age 62.5±10.3 years, 60 males), including 58 with mild cognitive impairment (MCI) and 44 with moderate or severe cognitive impairment (MSCI). The MRI images of these patients were subjected to z-score preprocessing, manual regions of interest (ROI) outlining, feature extraction (pyradiomics), feature selection [max-relevance and min-redundancy (mRMR), least absolute shrinkage and selection operator (LASSO), and univariate analysis], model construction (multivariate logistic regression), and evaluation [receiver operating characteristic curve (ROC), decision curve analysis (DCA), and calibration curves (CC)]. In the training dataset (71 patients, 44 MCI) and the test dataset (31 patients, 17 MCI), the area under curve (AUC) of the combined model (training 0.88 [95% CI 0.78, 0.97], test 0.76 [95% CI 0.6, 0.93]) was better than that of the clinical model and the radiomics model. The DCA results demonstrated the highest net yield of the combined model relative to the clinical and radiomics models. In addition, we found that LSA total vessel count (0.79 [95% CI 0.08, 1.59], P = 0.038) and wavelet.HLH_glcm_MCC (-1.2 [95% CI -2.2, -0.4], P = 0.008) were independent predictors of MCI. The model that combines clinical and radiomics features of LSA can predict MCI. Besides, LSA vascular parameters may serve as imaging biomarkers of cognitive impairment.

Silencing circLDLRAD3 Inhibits Lung Cancer Progression by Regulating the miR-497-5p/PFKP Axis

PURPOSE

Lung cancer is one of the leading causes of death worldwide. Recent studies have shown that circular RNAs are dysregulated in a variety of cancers, but the mechanism in lung cancer is still indistinct. In our work, we explored the action mechanism of circLDLRAD3 in lung cancer.

METHODS

The abundance of circLDLRAD3, microRNA-497-5p (miR-497-5p) and platelet-type PFK (PFKP) was measured by real-time quantitative polymerase chain reaction (RT-qPCR) in lung cancer. Meanwhile, the level of PFKP was quantified by western blot. Cell counting kit-8 (CCK-8), 5-Ethynyl-2'-deoxyuridine (EdU) assay, transwell assay, wound healing assay, flow cytometry, western blot, immunohistochemical (IHC) assay and glycolysis metabolism analysis were performed for functional analyses. Furthermore, the interplay between miR-497-5p and circLDLRAD3 or FKPF was detected by the dual-luciferase reporter and RNA Immunoprecipitation (RIP) assays. Eventually, the in vivo experiments were applied to measure the role of circLDLRAD3.

RESULT

The levels of circLDLRAD3 and PFKP were increased. Silencing circLDLRAD3 inhibited cell viability, proliferation, migration, invasion and glycolysis metabolism and promoted cell apoptosis in lung cancer cells. In mechanism, circLDLRAD3 regulated PFKP level as a miR-497-5p sponge. MiR-497-5p suppressed the progression of lung cancer by inhibiting PFKP. In addition, circLDLRAD3 knockdown also inhibited tumor growth in vivo.

CONCLUSION

CircLDLRAD3 promoted the development of lung cancer through increasing PFKP expression by regulating miR-497-5p, which also provided a potential targeted therapy for lung cancer treatment.

Development of a simultaneous quantification method of imatinib and sunitinib and their main metabolites and its application in patients with gastrointestinal stromal tumor

Correlations between plasma concentrations of imatinib and sunitinib with efficacy and toxicity have been established. It is crucial to develop a sensitive and precise method for determining the plasma concentrations of imatinib and sunitinib, along with their active metabolites, to facilitate therapeutic drug monitoring and individualized therapy. Plasma samples were separated on an Agilent ZORBAX SB-C18 chromatographic column using gradient elution. Quantification was performed using a mass spectrometer equipped with electrospray ionization in multiple reaction monitoring. The analysis time was 18 min per run, with all analytes and internal standards eluting within 8 min. The calibration range was 25-4000 ng/mL for imatinib, 5-800 ng/mL for N-desmethyl imatinib (CGP74588), and 2.5-400 ng/mL for sunitinib and N-desethyl sunitinib (SU12662). Intra- and inter-assay precision were both below 15%, and accuracy ranged between 90.0% and 101.9%. The method was successfully applied to determine blood samples from 120 patients with gastrointestinal stromal tumors who received imatinib (n = 115) and sunitinib (n = 5). It has been validated as linear, accurate, precise, and robust, making it suitable for therapeutic drug monitoring of imatinib and sunitinib in routine clinical practice.