4,327 research outputs found
Clinical study on the optic nerve protection of calcium dobesilate in treating glaucoma
AIM:To observe the protective effect of calcium dobesilate on optic nerve of glaucoma patients whose intraocular pressure has been under control through operation.<p>METHODS: A total of 78 inpatients(89 eyes)with glaucoma in this hospital from January, 2011 to February, 2012 were enrolled. All patients were randomly divided into treatment group and control group with 6 months in a course. The visual acuity, visual field(mean sensibility, MS), and intraocular pressure were measured at the experiment onset and 6 months later to evaluate the clinical effect.<p>RESULTS: There were no statistically significant differences in the visual acuity, intraocular pressure between the two groups neither at the experiment onset nor after 6 months(<i>P</i>>0.05). The mean sensibility(MS)of the treatment group was obviously improved(14.56±5.03 <i>vs </i>18.9±5.77, <i>P</i><0.05)with statistically significant differences before and after the treatment, while the MS remained unchanged in the control group(14.75±5.17 <i>vs </i>13.48±4.69). There are statistically significant difference between the treatment group and the control group. Compared to the ratio of improvement, stability, and deterioration in the control group(10.3%, 48.7%, 41.0%), the indexes were changed obviously in the treatment group(64.1%, 28.2%, 7.7%,<i>P</i><0.05)with statistically significant difference between the two groups.<p>CONCLUSION:Calcium dobesilate can improve mean retinal sensitivity and protect the optic nerve in glaucoma patients whose intraocular pressure has been controlled
SE-KGE: A Location-Aware Knowledge Graph Embedding Model for Geographic Question Answering and Spatial Semantic Lifting
Learning knowledge graph (KG) embeddings is an emerging technique for a
variety of downstream tasks such as summarization, link prediction, information
retrieval, and question answering. However, most existing KG embedding models
neglect space and, therefore, do not perform well when applied to (geo)spatial
data and tasks. For those models that consider space, most of them primarily
rely on some notions of distance. These models suffer from higher computational
complexity during training while still losing information beyond the relative
distance between entities. In this work, we propose a location-aware KG
embedding model called SE-KGE. It directly encodes spatial information such as
point coordinates or bounding boxes of geographic entities into the KG
embedding space. The resulting model is capable of handling different types of
spatial reasoning. We also construct a geographic knowledge graph as well as a
set of geographic query-answer pairs called DBGeo to evaluate the performance
of SE-KGE in comparison to multiple baselines. Evaluation results show that
SE-KGE outperforms these baselines on the DBGeo dataset for geographic logic
query answering task. This demonstrates the effectiveness of our
spatially-explicit model and the importance of considering the scale of
different geographic entities. Finally, we introduce a novel downstream task
called spatial semantic lifting which links an arbitrary location in the study
area to entities in the KG via some relations. Evaluation on DBGeo shows that
our model outperforms the baseline by a substantial margin.Comment: Accepted to Transactions in GI
Clinical analysis of high myopia in 320 cases in Ningxia Hui Autonomous Region
AIM: To analyze the clinical manifestations and etiological factors of high myopia in 320 cases. <p>METHODS:A total of 320 patients(640 eyes)with high myopia treated in Ningxia Eye Hospital from January 2011 to November 2012 were studied. All of them underwent thorough eye examination and relevant environmental factors were recorded. The following data were analyzed, including gender, ethnicity, age of onset, refractive error, axial length, best corrected visual acuity(BCVA), educational level and living environment. <p>RESULTS: Bilateral high myopia was present in 320 patients(130 men and 190 women; 250 being of Han nationality and 70 of Hui nationality)with a mean age of 42.65±16.51 years(range: 3-80 years); the male to female ratio was 1:1.5. The age of onset was lower than 20 years in 237 patients, higher than 21 yeas in 83 patients, the difference was statistically significant(<i>P</i><0.001). There was no significant difference between diopter and educational level(<i>P</i>>0.05). The patients with BCVA higher than 0.3 increased with diopter increased, while BCVA lower than 0.8 and between 0.4~0.7 reduced. Refraction was significantly negatively correlated with BCVA(<i>r</i>=-0.196, <i>P</i><0.05)and positive correlated with axial length(<i>r</i>=0.681, <i>P</i><0.05). <p>CONCLUSION: In the study, patients with high myopia tend to have early onset, low educational level, and spacious living environment. Such results indicate that the genetic factors may be the main cause of high myopia in this group. The higher the degree of myopia was, the worse BCVA and the longer AL would be
Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells
Unsupervised text encoding models have recently fueled substantial progress
in NLP. The key idea is to use neural networks to convert words in texts to
vector space representations based on word positions in a sentence and their
contexts, which are suitable for end-to-end training of downstream tasks. We
see a strikingly similar situation in spatial analysis, which focuses on
incorporating both absolute positions and spatial contexts of geographic
objects such as POIs into models. A general-purpose representation model for
space is valuable for a multitude of tasks. However, no such general model
exists to date beyond simply applying discretization or feed-forward nets to
coordinates, and little effort has been put into jointly modeling distributions
with vastly different characteristics, which commonly emerges from GIS data.
Meanwhile, Nobel Prize-winning Neuroscience research shows that grid cells in
mammals provide a multi-scale periodic representation that functions as a
metric for location encoding and is critical for recognizing places and for
path-integration. Therefore, we propose a representation learning model called
Space2Vec to encode the absolute positions and spatial relationships of places.
We conduct experiments on two real-world geographic data for two different
tasks: 1) predicting types of POIs given their positions and context, 2) image
classification leveraging their geo-locations. Results show that because of its
multi-scale representations, Space2Vec outperforms well-established ML
approaches such as RBF kernels, multi-layer feed-forward nets, and tile
embedding approaches for location modeling and image classification tasks.
Detailed analysis shows that all baselines can at most well handle distribution
at one scale but show poor performances in other scales. In contrast,
Space2Vec's multi-scale representation can handle distributions at different
scales.Comment: 15 pages; Accepted to ICLR 2020 as a spotlight pape
Transcriptional up-regulation of relaxin-3 by Nur77 attenuates β-adrenergic agonist-induced apoptosis in cardiomyocytes.
The relaxin family peptides have been shown to exert several beneficial effects on the heart, including anti-apoptosis, anti-fibrosis, and anti-hypertrophy activity. Understanding their regulation might provide new opportunities for therapeutic interventions, but the molecular mechanism(s) coordinating relaxin expression in the heart remain largely obscured. Previous work demonstrated a role for the orphan nuclear receptor Nur77 in regulating cardiomyocyte apoptosis. We therefore investigated Nur77 in the hopes of identifying novel relaxin regulators. Quantitative real-time PCR (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA) data indicated that ectopic expression of orphan nuclear receptor Nur77 markedly increased the expression of latexin-3 (RLN3), but not relaxin-1 (RLN1), in neonatal rat ventricular cardiomyocytes (NRVMs). Furthermore, we found that the -adrenergic agonist isoproterenol (ISO) markedly stimulated RLN3 expression, and this stimulation was significantly attenuated in Nur77 knockdown cardiomyocytes and Nur77 knockout hearts. We showed that Nur77 significantly increased RLN3 promoter activity via specific binding to the RLN3 promoter, as demonstrated by electrophoretic mobility shift assay (EMSA) and chromatin immuno-precipitation (ChIP) assays. Furthermore, we found that Nur77 overexpression potently inhibited ISO-induced cardiomyocyte apoptosis, whereas this protective effect was significantly attenuated in RLN3 knockdown cardiomyocytes, suggesting that Nur77-induced RLN3 expression is an important mediator for the suppression of cardiomyocyte apoptosis. These findings show that Nur77 regulates RLN3 expression, therefore suppressing apoptosis in the heart, and suggest that activation of Nur77 may represent a useful therapeutic strategy for inhibition of cardiac fibrosis and heart failure. © 2018 You et al
Radio AGN Selection and Characterization in Three Deep-Drilling Fields of the Vera C. Rubin Observatory Legacy Survey of Space and Time
The Australia Telescope Large Area Survey (ATLAS) and the VLA survey in the
XMM-LSS/VIDEO deep field provide deep ( Jybeam) and
high-resolution ( 4.5--8 arcsec) radio coverage of the three XMM-SERVS
fields (W-CDF-S, ELAIS-S1, and XMM-LSS). These data cover a total sky area of
11.3 deg and contain radio components. Furthermore, about
3~deg of the XMM-LSS field also has deeper MIGHTEE data that achieve a
median RMS of 5.6 Jy beam and detect more than 20000 radio
sources. We analyze all these radio data and find source counterparts at other
wavebands utilizing deep optical and IR surveys. The nature of these radio
sources is studied using radio-band properties (spectral slope and morphology),
and the IR-radio correlation. %and spectral energy distribution. Radio AGNs are
selected and compared with those selected using other methods (e.g. X-ray). We
found 1656 new AGNs that were not selected using X-ray and/or MIR methods. We
constrain the FIR-to-UV SEDs of radio AGNs using {\sc cigale} and investigate
the dependence of radio AGN fraction upon galaxy stellar mass and
star-formation rate.Comment: 25 pages, 21+3 figures, 8+1 tables, MNRAS accepted (final version).
The catalogues are available from
https://personal.psu.edu/wnb3/xmmservs/zhu2023-tables-2023-04-12.tar.zi
基于Scopus的植物表型组学研究进展分析
Bibliometric analyses are capable of demonstrating the history and the tendency of scientific and technological development. This article aims to use big scientific data to explore the present status of plant phenomics, based on which sound recommendations could be provided for the development of this emerging research domain. [Methods] Based on academic outputs such as research publications, citations, collaborations, research areas, academic organizations, and authors retrieved from the Scopus database between 2013 and September 2018, statistical analysis tools such as SciVal and CiteSpace 5.0 were applied to quantitatively visualize the development and tendency of plant phenotyping, plant phenomics, and related research areas. [Results] This Scopus-based research has retrieved 20 953 articles that are related to plant phenotyping, plant phenomics, and related applications in plant research, with a total citation of 217 105 and 2.0% of them are TOP1% highly cited papers. According to total citations, the TOP10 countries are the United States, China, Germany, the United Kingdom, France, Japan, Australia, Spain, Canada, and the Netherlands. The TOP10 research organizations based on total citations are Chinese Academy of Sciences (CAS), Institut National de la Recherche Agronomique (INRA), the US Department of Agriculture, Centre National de la Recherche Scientifique (CNRS), Chinese Academy of Agricultural Sciences, Cornell University, Spanish National Research Council, University of California at Davis, Universite Paris-Sacly, and Wageningen University & Research. The scholar with the most academic outputs is Alisdair Robert Fernie at the Koch Planck Institute of Molecular Plant Physiology, Germany. He has published 58 papers using plant cellular phenotypes and was cited 1 246 times. At present, plant phenomics research has focused on a number of plant species, including Arabidopsis, rice, wheat, corn, tomato and soybean. [Conclusion] As an emerging research domain, plant phenomics requires interdisciplinary efforts to integrate agriculture, cultivation, breeding, and other plant biological research with computing sciences. In particular, high-throughput image analysis and related data analysis has become an important research theme at the present stage, with the topical saliency index reaches 98.8%, a very high relevance score
Crosstalk between Platelets and the Immune System: Old Systems with New Discoveries
Platelets are small anucleate cells circulating in the blood. It has been recognized for more than 100 years that platelet adhesion and aggregation at the site of vascular injury are critical events in hemostasis and thrombosis; however, recent studies demonstrated that, in addition to these classic roles, platelets also have important functions in inflammation and the immune response. Platelets contain many proinflammatory molecules and cytokines (e.g., P-selectin, CD40L, IL-1β, etc.), which support leukocyte trafficking, modulate immunoglobulin class switch, and germinal center formation. Platelets express several functional Toll-like receptors (TLRs), such as TLR-2, TLR-4, and TLR-9, which may potentially link innate immunity with thrombosis. Interestingly, platelets also contain multiple anti-inflammatory molecules and cytokines (e.g., transforming growth factor-β and thrombospondin-1). Emerging evidence also suggests that platelets are involved in lymphatic vessel development by directly interacting with lymphatic endothelial cells through C-type lectin-like receptor 2. Besides the active contributions of platelets to the immune system, platelets are passively targeted in several immune-mediated diseases, such as autoimmune thrombocytopenia, infection-associated thrombocytopenia, and fetal and neonatal alloimmune thrombocytopenia. These data suggest that platelets are important immune cells and may contribute to innate and adaptive immunity under both physiological and pathological conditions
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