Infrared-Improved Soft-wall AdS/QCD Model for Mesons

We construct and investigate an infrared-improved soft-wall AdS/QCD model for mesons. Both linear confinement and chiral symmetry breaking of low energy QCD are well characterized in such an infrared-improved soft-wall AdS/QCD model. The model enables us to obtain a more consistent numerical prediction for the mass spectra of resonance scalar, pseudoscalar, vector and axial-vector mesons. In particular, the predicted mass for the lightest ground state scalar meson shows a good agreement with the experimental data. The model also provides a remarkable check for the Gell-Mann-Oakes-Renner relation and a sensible result for the space-like pion form factor.Comment: 15 pages, 4 figures, 7 tables, published versio

UniKG: A Benchmark and Universal Embedding for Large-Scale Knowledge Graphs

Irregular data in real-world are usually organized as heterogeneous graphs (HGs) consisting of multiple types of nodes and edges. To explore useful knowledge from real-world data, both the large-scale encyclopedic HG datasets and corresponding effective learning methods are crucial, but haven't been well investigated. In this paper, we construct a large-scale HG benchmark dataset named UniKG from Wikidata to facilitate knowledge mining and heterogeneous graph representation learning. Overall, UniKG contains more than 77 million multi-attribute entities and 2000 diverse association types, which significantly surpasses the scale of existing HG datasets. To perform effective learning on the large-scale UniKG, two key measures are taken, including (i) the semantic alignment strategy for multi-attribute entities, which projects the feature description of multi-attribute nodes into a common embedding space to facilitate node aggregation in a large receptive field; (ii) proposing a novel plug-and-play anisotropy propagation module (APM) to learn effective multi-hop anisotropy propagation kernels, which extends methods of large-scale homogeneous graphs to heterogeneous graphs. These two strategies enable efficient information propagation among a tremendous number of multi-attribute entities and meantimes adaptively mine multi-attribute association through the multi-hop aggregation in large-scale HGs. We set up a node classification task on our UniKG dataset, and evaluate multiple baseline methods which are constructed by embedding our APM into large-scale homogenous graph learning methods. Our UniKG dataset and the baseline codes have been released at https://github.com/Yide-Qiu/UniKG.Comment: 9 pages, 4 figure

Characterizing the Blood Oxygen Level-Dependent Fluctuations in Musculoskeletal Tumours Using Functional Magnetic Resonance Imaging

This study characterized the blood oxygen level-dependent (BOLD) fluctuations in benign and malignant musculoskeletal tumours via power spectrum analyses in pre-established low-frequency bands. BOLD MRI and T1-weighted imaging (T1WI) were collected for 52 patients with musculoskeletal tumours. Three ROIs were drawn on the T1WI image in the tumours’ central regions, peripheral regions and neighbouring tissue. The power spectrum of the BOLD within each ROI was calculated and divided into the following four frequency bands: 0.01–0.027 Hz, 0.027–0.073 Hz, 0.073–0.198 Hz, and 0.198–0.25 Hz. ANOVA was conducted for each frequency band with the following two factors: the location of the region of interest (LoR, three levels: tumour “centre”, “peripheral” and “healthy tissue”) and tumour characteristic (TC, two levels: “malignant” and “benign”). There was a significant main effect of LoR in the frequencies of 0.073–0.198 Hz and 0.198–0.25 Hz. These data were further processed with post-hoc pair-wise comparisons. BOLD fluctuations at 0.073–0.198 Hz were stronger in the peripheral than central regions of the malignant tumours; however, no such difference was observed for the benign tumours. Our findings provide evidence that the BOLD signal fluctuates with spatial heterogeneity in malignant musculoskeletal tumours at the frequency band of 0.073–0.198 Hz

An investigation of the health value and self-care capabilities of the elderly in urban-rural fringe area nursing homes and the related influencing factors

AbstractObjectiveTo investigate the health value and self-care capabilities of the elderly living in urban-rural fringe area nursing homes and the factors that influence these variables.MethodsA cluster sampling method was used to select 280 elderly individuals from seven urban-rural fringe communities in Xianning to complete a survey regarding their health value and self-care capabilities.ResultsThe total health value and self-care capability scores of the elderly were 7.45 ± 1.45 and 100.25 ± 22.56, respectively. Both of these scores significantly differed by age, education level, marital status, and income (P < 0.05, P < 0.01). Self-care capability was correlated with health value (r = 0.521). A multivariate linear regression analysis showed that health value, marital status, and age predicted self-care capability.ConclusionsElderly people living in the urban-rural fringe area with higher health values also had higher self-care capabilities. The self-care capabilities of the elderly can be enhanced by improving their health value using the “knowing-trusting-acting” model

Scaling Behavior of the Quantum Phase Transition from a Quantum Anomalous Hall Insulator to an Axion Insulator

The phase transitions from one plateau to the next plateau or to an insulator in quantum Hall and quantum anomalous Hall (QAH) systems have revealed universal scaling behaviors. A magnetic-field-driven quantum phase transition from a QAH insulator to an axion insulator was recently demonstrated in magnetic topological insulator sandwich samples. Here, we show that the temperature dependence of the derivative of the longitudinal resistance on magnetic field at the transition point follows a characteristic power-law that indicates a universal scaling behavior for the QAH to axion insulator phase transition. Similar to the quantum Hall plateau to plateau transition, the QAH to axion insulator transition can also be understood by the Chalker-Coddington network model. We extract a critical exponent k~ 0.38 in agreement with recent high-precision numerical results on the correlation length exponent of the Chalker-Coddington model at v ~ 2.6, rather than the generally-accepted value of 2.33.Comment: 24 pages, 4 figures, comments are welcom

Biofortification of different maize cultivars with zinc, iron and selenium by foliar fertilizer applications

Fertilizer-based biofortification is a strategy for combating worldwide malnutrition of zinc (Zn), iron (Fe) and selenium (Se). Field experiments were conducted to investigate the effects of foliar treatments on concentrations of Zn, Fe, Se, N and bioavailability of Zn and Fe in grains of three maize cultivars grown at three locations. We compared the efficacy of ZnO nanoparticles (ZnO-NPs), Zn complexed chitosan nanoparticles (Zn-CNPs), conventional ZnSO4 and a cocktail solution (containing Zn, Fe and Se). All treatments were foliar-applied at rate of 452 mg Zn L–1, plus urea. Applying ten-fold less Zn (at rate of 45.2 mg Zn L–1) plus urea in the form of ZnO-NPs, Zn-CNPs, or ZnSO4 resulted in no increase, or a negligible increase, in grain Zn concentration compared with deionized water. By contrast, among the different Zn sources plus urea applied by foliar sprays, conventional ZnSO4 was the most efficient in improving grain Zn concentration. Furthermore, foliar application of a cocktail solution effectively improved grain concentrations of Zn, Fe, Se and N simultaneously, without a grain yield trade-off. For example, the average grain concentrations were simultaneously increased from 13.8 to 22.1 mg kg–1 for Zn, from 17.2 to 22.1 mg kg–1for Fe, from 21.4 to 413.5 ug kg–1 for Se and from 13.8 to 14.7 g kg–1 for N by foliar application of a cocktail solution. Because grain yield was significantly negatively correlated with grain nutrient concentrations, the magnitude of increase in grain concentrations of Zn and Fe was most pronounced in the maize cultivar with the lowest grain yield (Zhengdan958 grown in Linyi). Foliar application of a cocktail solution also significantly decreased the phytic acid (PA) concentration, ratios of PA/Fe and PA/Zn in grains, indicating an increased bioavailability of Fe and Zn for human health. In conclusion, we found that a foliar application of a cocktail solution including Zn, Fe, Se and N was most effective for biofortification, but that the grains with the lowest yield contained the greatest concentration of these elements. This finding highlights the need to breed maize varieties that are capable of achieving both high grain yield and high grain nutritional quality to address food security and human health challenges

Bioinformatics-based analysis reveals elevated CYTL1 as a potential therapeutic target for BRAF-mutated melanoma

Introduction: Despite many recent emerging therapeutic modalities that have prolonged the survival of melanoma patients, the prognosis of melanoma remains discouraging, and further understanding of the mechanisms underlying melanoma progression is needed. Melanoma patients often have multiple genetic mutations, with BRAF mutations being the most common. In this study, public databases were exploited to explore a potential therapeutic target for BRAF-mutated melanoma.Methods: In this study, we analyzed differentially expressed genes (DEGs) in normal tissues and melanomas, Braf wild-type and Braf mutant melanomas using information from TCGA databases and the GEO database. Subsequently, we analyzed the differential expression of CYTL1 in various tumor tissues and its effect on melanoma prognosis, and resolved the mutation status of CYTL1 and its related signalling pathways. By knocking down CYTL1 in melanoma cells, the effects of CYTL1 on melanoma cell proliferation, migration and invasion were further examined by CCK8 assay, Transwell assay and cell migration assay.Results: 24 overlapping genes were identified by analyzing DEGs common to melanoma and normal tissue, BRAF-mutated and BRAF wild-type melanoma. Among them, CYTL1 was highly expressed in melanoma, especially in BRAF-mutated melanoma, and the high expression of CYTL1 was associated with epithelial-mesenchymal transition (EMT), cell cycle, and cellular response to UV. In melanoma patients, especially BRAF-mutated melanoma patients, clinical studies showed a positive correlation between increased CYTL1 expression and shorter overall survival (OS) and disease-free survival (DFS). In vitro experiments further confirmed that the knockdown of CYTL1 significantly inhibited the migration and invasive ability of melanoma cells.Conclusion: CYTL1 is a valuable prognostic biomarker and a potentially effective therapeutic target in melanoma, especially BRAF-mutated melanoma

Experimental observation of quantum state-independent contextuality under no-signaling conditions

Contextuality, the impossibility of assigning context-independent measurement outcomes, is a critical resource for quantum computation and communication. No-signaling betweensuccessivemeasurementsisanessentialrequirementthatshouldbeaccomplishedin anytestofquantumcontextualityandthatisdifficulttoachieveinpractice.Here,weintroduce anoptimalquantumstate-independentcontextualityinequalityinwhichthedeviationfromthe classicalboundismaximal.Wethenexperimentallytestitusingsinglephotonsgeneratedfrom a defect in a bulk silicon carbide, while satisfying the requirement of no-signaling within the experimental error. Our results shed new light on the study of quantum contextuality under no-signalingconditions

Toll-Like Receptor 7 Enhances Rabies Virus-Induced Humoral Immunity by Facilitating the Formation of Germinal Centers

Rabies virus (RABV) causes fatal encephalitis in mammals and poses a public health threat in many parts of the world. Vaccination remains the most effective means for prevention and control of rabies. Studies focusing on the mechanism of RABV immunogenicity are necessary for improvement of rabies vaccines. Toll-like receptor 7 (TLR7), an innate receptor sensing single-stranded viral RNA, is important for the induction of innate and adaptive immunity. Our studies revealed that the absence of TLR7 led to a lower antibody production in mice immunized with RABV. It is further found that TLR7 deficiency affected the recruitment of germinal center (GC) B cells and led to lessened GCs formation. Consistently, there were less plasma cells (PCs) and antibody secreting cells (ASC) in TLR7−/− mice than those in wild type (WT) mice, resulting in impaired production of RABV-neutralizing antibodies (VNA). TLR7 deficiency also impaired the generation of memory B cells (MBCs) and the induction of secondary immune responses. Moreover, TLR7 deficiency down-regulated the induction of some cytokines/chemokines, especially IFN-γ, resulting in a Th2-biased antibody production. Overall, our results suggest that TLR7 facilitates the induction of the humoral immunity in response to RABV