Network pharmacology and UPLC-Q-TOF/MS studies on the anti-arthritic mechanism of Pterocephalus hookeri

Purpose: To investigate the mechanism underlying the anti-arthritic properties of Pterocephalus hookeri used for treatment of rheumatoid arthritis (RA).Methods: Aqueous methanol extract of P. hookeri was analyzed using UPLC-Q-TOF/MS, a Waters Acquity UPLCR BEH C18 column (2.1 × 100 mm, 1.7 μm) and gradient elution with acetonitrile-formic acid-water. Targets and related pathways were predicted by PharmMapper database and Molecule Annotation System, respectively. The network was built with Cytoscape software.Results: Forty compounds were identified, comprising 17 iridoid glycosides, 7 phenolic acids, 13 triterpenes, and 3 other compounds. A total of 38 targets and 44 pathways associated with RA were obtained. These involved mainly MAPK signaling pathway, adherens junction, and colorectal cancer.Conclusion: These results from network pharmacology suggest that P. hookeri exerts therapeutic effect on RA via multiple components, multiple targets and multiple pathways.Keywords: Pterocephalus hookeri, Rheumatoid arthritis, UPLC-Q-TOF/MS, Chemical composition, Network pharmacolog

Application of Deep Learning Methods for Distinguishing Gamma-Ray Bursts from Fermi/GBM TTE Data

To investigate GRBs in depth, it is crucial to develop an effective method for identifying GRBs accurately. Current criteria, e.g., onboard blind search, ground blind search, and target search, are limited by manually set thresholds and perhaps miss GRBs, especially for sub-threshold events. We propose a novel approach that utilizes convolutional neural networks (CNNs) to distinguish GRBs and non-GRBs directly. We structured three CNN models, plain-CNN, ResNet, and ResNet-CBAM, and endeavored to exercise fusing strategy models. Count maps of NaI detectors onboard Fermi/GBM were employed as the input samples of datasets and models were implemented to evaluate their performance on different time scale data. The ResNet-CBAM model trained on 64 ms dataset achieves high accuracy overall, which includes residual and attention mechanism modules. The visualization methods of Grad-CAM and t-SNE explicitly displayed that the optimal model focuses on the key features of GRBs precisely. The model was applied to analyze one-year data, accurately identifying approximately 98% of GRBs listed in the Fermi burst catalog, 8 out of 9 sub-threshold GRBs, and 5 GRBs triggered by other satellites, which demonstrated the deep learning methods could effectively distinguish GRBs from observational data. Besides, thousands of unknown candidates were retrieved and compared with the bursts of SGR J1935+2154 for instance, which exemplified the potential scientific value of these candidates indeed. Detailed studies on integrating our model into real-time analysis pipelines thus may improve their accuracy of inspection, and provide valuable guidance for rapid follow-up observations of multi-band telescopes.Comment: accepted for publication in ApJSS. 45 pages,17 figure

Self-doping effect in confined copper selenide semiconducting quantum dots for efficient photoelectrocatalytic oxygen evolution

Self-doping can not only suppress the photogenerated charge recombination of semiconducting quantum dots by self-introducing trapping states within the bandgap, but also provide high-density catalytic active sites as the consequence of abundant non-saturated bonds associated with the defects. Here, we successfully prepared semiconducting copper selenide (CuSe) confined quantum dots with abundant vacancies and systematically investigated their photoelectrochemical characteristics. Photoluminescence characterizations reveal that the presence of vacancies reduces the emission intensity dramatically, indicating a low recombination rate of photogenerated charge carriers due to the self-introduced trapping states within the bandgap. In addition, the ultra-low charge transfer resistance measured by electrochemical impedance spectroscopy implies the efficient charge transfer of CuSe semiconducting quantum dots-based photoelectrocatalysts, which is guaranteed by the high conductivity of their confined structure as revealed by room-temperature electrical transport measurements. Such high conductivity and low photogenerated charge carriers recombination rate, combined with high-density active sites and confined structure, guaranteeing the remarkable photoelectrocatalytic performance and stability as manifested by photoelectrocatalysis characterizations. This work promotes the development of semiconducting quantum dots-based photoelectrocatalysis and demonstrates CuSe semiconducting quantum confined catalysts as an advanced photoelectrocatalysts for oxygen evolution reaction

Head-mounted Sensory Augmentation Device: Comparing Haptic and Audio Modality

This paper investigates and compares the effectiveness of haptic and audio modality for navigation in low visibility environment using a sensory augmentation device. A second generation head-mounted vibrotactile interface as a sensory augmentation prototype was developed to help users to navigate in such environments. In our experiment, a subject navigates along a wall relying on the haptic or audio feedbacks as navigation commands. Haptic/audio feedback is presented to the subjects according to the information measured from the walls to a set of 12 ultrasound sensors placed around a helmet and a classification algorithm by using multilayer perceptron neural network. Results showed the haptic modality leads to significantly lower route deviation in navigation compared to auditory feedback. Furthermore, the NASA TLX questionnaire showed that subjects reported lower cognitive workload with haptic modality although both modalities were able to navigate the users along the wall

Role of macrophage sialoadhesin in host defense against the sialylated pathogen group B <em>Streptococcus</em>

ABSTRACT: Several bacterial pathogens decorate their surfaces with sialic acid (Sia) residues within cell wall components or capsular exopolysaccharides. Sialic acid expression can promote bacterial virulence by blocking complement activation or by engagement of inhibitory sialic acid-binding immunoglobulin-like lectins (Siglecs) on host leukocytes. Expressed at high levels on splenic and lymph node macrophages, sialoadhesin (Sn) is a unique Siglec with an elongated structure that lacks intracellular signaling motifs. Sialoadhesin allows macrophage to engage certain sialylated pathogens and stimulate inflammatory responses, but the in vivo significance of sialoadhesin in infection has not been shown. We demonstrate that macrophages phagocytose the sialylated pathogen group B Streptococcus (GBS) and increase bactericidal activity via sialoadhesin-sialic-acid-mediated recognition. Sialoadhesin expression on marginal zone metallophillic macrophages in the spleen trapped circulating GBS and restricted the spread of the GBS to distant organs, reducing mortality. Specific IgM antibody responses to GBS challenge were also impaired in sialoadhesin-deficient mice. Thus, sialoadhesin represents a key bridge to orchestrate innate and adaptive immune defenses against invasive sialylated bacterial pathogens. KEY MESSAGE: Sialoadhesin is critical for macrophages to phagocytose and clear GBS. Increased GBS organ dissemination in the sialoadhesin-deficient mice. Reduced anti-GBS IgM production in the sialoadhesin-deficient mice. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00109-014-1157-y) contains supplementary material, which is available to authorized users

The development of carbon dots: From the perspective of materials chemistry

The advance of materials chemistry has influenced significantly the lifestyle of mankind. By virtue of their fascinating physicochemical nature – including ultrasmall size (<10 nm), rich functional groups, fluorescence, chemical stability, biocompatibility, and nontoxicity – carbon dots have been acclaimed as another epoch-making carbon-based nanomaterial following on from fullerene, nanotubes, and graphene. However, the field of carbon dot-based materials chemistry remains incomplete because of their wide structural diversity, meaning that much fundamental knowledge still needs to be uncovered. Herein, this review proposed several novel viewpoints in term of carbon dot-based material chemistry, including the development history, classification, design principle and applications of carbon dots-based materials. Finally, several sound prospects in this fascinating filed are also given

Improved annotation of 3' untranslated regions and complex loci by combination of strand-specific direct RNA sequencing, RNA-seq and ESTs

The reference annotations made for a genome sequence provide the framework for all subsequent analyses of the genome. Correct annotation is particularly important when interpreting the results of RNA-seq experiments where short sequence reads are mapped against the genome and assigned to genes according to the annotation. Inconsistencies in annotations between the reference and the experimental system can lead to incorrect interpretation of the effect on RNA expression of an experimental treatment or mutation in the system under study. Until recently, the genome-wide annotation of 3-prime untranslated regions received less attention than coding regions and the delineation of intron/exon boundaries. In this paper, data produced for samples in Human, Chicken and A. thaliana by the novel single-molecule, strand-specific, Direct RNA Sequencing technology from Helicos Biosciences which locates 3-prime polyadenylation sites to within +/- 2 nt, were combined with archival EST and RNA-Seq data. Nine examples are illustrated where this combination of data allowed: (1) gene and 3-prime UTR re-annotation (including extension of one 3-prime UTR by 5.9 kb); (2) disentangling of gene expression in complex regions; (3) clearer interpretation of small RNA expression and (4) identification of novel genes. While the specific examples displayed here may become obsolete as genome sequences and their annotations are refined, the principles laid out in this paper will be of general use both to those annotating genomes and those seeking to interpret existing publically available annotations in the context of their own experimental dataComment: 44 pages, 9 figure