EMAGE mouse embryo spatial gene expression database: 2014 update.

EMAGE (http://www.emouseatlas.org/emage/) is a freely available database of in situ gene expression patterns that allows users to perform online queries of mouse developmental gene expression. EMAGE is unique in providing both text-based descriptions of gene expression plus spatial maps of gene expression patterns. This mapping allows spatial queries to be accomplished alongside more traditional text-based queries. Here, we describe our recent progress in spatial mapping and data integration. EMAGE has developed a method of spatially mapping 3D embryo images captured using optical projection tomography, and through the use of an IIP3D viewer allows users to view arbitrary sections of raw and mapped 3D image data in the context of a web browser. EMAGE now includes enhancer data, and we have spatially mapped images from a comprehensive screen of transgenic reporter mice that detail the expression of mouse non-coding genomic DNA fragments with enhancer activity. We have integrated the eMouseAtlas anatomical atlas and the EMAGE database so that a user of the atlas can query the EMAGE database easily. In addition, we have extended the atlas framework to enable EMAGE to spatially cross-index EMBRYS whole mount in situ hybridization data. We additionally report on recent developments to the EMAGE web interface, including new query and analysis capabilities.

Clonal and molecular analysis of the prospective anterior neural boundary in the mouse embryo.

In the mouse embryo the anterior ectoderm undergoes extensive growth and morphogenesis to form the forebrain and cephalic non-neural ectoderm. We traced descendants of single ectoderm cells to study cell fate choice and cell behaviour at late gastrulation. In addition, we provide a comprehensive spatiotemporal atlas of anterior gene expression at stages crucial for anterior ectoderm regionalisation and neural plate formation. Our results show that, at late gastrulation stage, expression patterns of anterior ectoderm genes overlap significantly and correlate with areas of distinct prospective fates but do not define lineages. The fate map delineates a rostral limit to forebrain contribution. However, no early subdivision of the presumptive forebrain territory can be detected. Lineage analysis at single-cell resolution revealed that precursors of the anterior neural ridge (ANR), a signalling centre involved in forebrain development and patterning, are clonally related to neural ectoderm. The prospective ANR and the forebrain neuroectoderm arise from cells scattered within the same broad area of anterior ectoderm. This study establishes that although the segregation between non-neural and neural precursors in the anterior midline ectoderm is not complete at late gastrulation stage, this tissue already harbours elements of regionalisation that prefigure the later organisation of the head.

[Relationship between hepatitis B surface antigen, HBV DNA quantity and liver fibrosis severity].

OBJECTIVE: To explore the correlation between serum hepatitis B surface antigen (HBsAg) level and hepatic tissue pathological staging in patients with chronic hepatitis B (CHB). METHODS: Clinical data was collected from our hospital's records for 302 CHB patients with HBsAg-positive status for more than 6 months and who had undergone hepatic biopsy. The HBsAg level,HBV DNA level and other clinical data were measured using commercial diagnostic assays. Liver histology was scored using the GS staging system. Correlation between serum HBsAg quantity, HBV DNA quantity, stage of inflammation and degree of fibrosis was assessed statistically. RESULTS: The correlation of serum HBsAg level and HBV DNA level was notable. The serum HBsAg level was a variable affecting hepatic tissue pathological stage significantly. Serum HBsAg level appeared to be a highly specific and sensitive diagnostic marker of hepatic fibrosis. As the severity of liver fibrosis increased, the quantitative levels of platelet (PLT), HBsAg and HBV DNA gradually decreased, and the APRI index gradually increased; there were significant differences between the groups (all P<0.001). Serum HBsAg and HBV DNA levels in patients with hepatitis B e antigen-positive (HBeAg(+)) status showed strong correlation (r=0.721, P<0.0001) by Spearman analysis. HBeAg(+) patients with moderate to severe fibrosis (S2-4) exhibited significantly lower serum HBsAg and HBV DNA levels compared with patients with no or mild fibrosis (S0-1; t=5.475 and 4.826, P<0.001). ROC analysis suggested that a serum HBsAg cutoff of 4.46 log 10 IU/mL (28 800 IU/mL) would provide a theoretical sensitivity of 76.3%, with theoretical specificity of 70.5% in HBeAg(+) CHB patients. A serum HBV DNA cutoff of 7.13 log 10 IU/mL (1.35*10(7) copies/mL) would provide a theoretical sensitivity of 71.1%, with theoretical specificity of 73.4% in HBeAg(+) CHB patients. Logistic regression analysis showed that the level of HBsAg was an independent prognostic factor of moderate to severe liver fibrosis, with alanine aminotransferase, aspartate aminotransferase, HBsAg, HBV DNA and PLT (P<0.001). CONCLUSION: HBsAg and HBV DNA levels decrease gradually along with aggravation of liver fibrosis. The cutoff values of 28800 IU/mL for HBsAg and 1.35*10(7) copies/mL ofHBV DNA provide higher specificity and sensitivity for predicting the degree of liver fibrosis in HBeAg-positive CHB patients, and the former is an independent predictor of severe liver fibrosis.

eMouseAtlas, EMAGE, and the spatial dimension of the transcriptome.

eMouseAtlas (www.emouseatlas.org) is a comprehensive online resource to visualise mouse development and investigate gene expression in the mouse embryo. We have recently deployed a completely redesigned Mouse Anatomy Atlas website (www.emouseatlas.org/emap/ema) that allows users to view 3D embryo reconstructions, delineated anatomy, and high-resolution histological sections. A new feature of the website is the IIP3D web tool that allows a user to view arbitrary sections of 3D embryo reconstructions using a web browser. This feature provides interactive access to very high-volume 3D images via a tiled pan-and-zoom style interface and circumvents the need to download large image files for visualisation. eMouseAtlas additionally includes EMAGE (Edinburgh Mouse Atlas of Gene Expression) (www.emouseatlas.org/emage), a freely available, curated online database of in situ gene expression patterns, where gene expression domains extracted from raw data images are spatially mapped into atlas embryo models. In this way, EMAGE introduces a spatial dimension to transcriptome data and allows exploration of the spatial similarity between gene expression patterns. New features of the EMAGE interface allow complex queries to be built, and users can view and compare multiple gene expression patterns. EMAGE now includes mapping of 3D gene expression domains captured using the imaging technique optical projection tomography. 3D mapping uses WlzWarp, an open-source software tool developed by eMouseAtlas.

EMAGE mouse embryo spatial gene expression database: 2010 update.

EMAGE (http://www.emouseatlas.org/emage) is a freely available online database of in situ gene expression patterns in the developing mouse embryo. Gene expression domains from raw images are extracted and integrated spatially into a set of standard 3D virtual mouse embryos at different stages of development, which allows data interrogation by spatial methods. An anatomy ontology is also used to describe sites of expression, which allows data to be queried using text-based methods. Here, we describe recent enhancements to EMAGE including: the release of a completely re-designed website, which offers integration of many different search functions in HTML web pages, improved user feedback and the ability to find similar expression patterns at the click of a button; back-end refactoring from an object oriented to relational architecture, allowing associated SQL access; and the provision of further access by standard formatted URLs and a Java API. We have also increased data coverage by sourcing from a greater selection of journals and developed automated methods for spatial data annotation that are being applied to spatially incorporate the genome-wide (approximately 19,000 gene) 'EURExpress' dataset into EMAGE.

Laboratory predictors of severe Coronavirus Disease 2019 and lung function in followed-up.

BACKGROUND: A pandemic caused by SARS-CoV-2 has infected more than 79 million people and killed exceeding 1.7 million people around the world by the end of 2020. METHOD: We obtained the clinical data of all diagnosed patients and lung function test of followed-up patients in Fuyang, Anhui province to investigate laboratory predictors of severe Coronavirus Disease 2019 (COVID-19) and the impairment of lung function. RESULTS: Of the 155 patients, 87 (56.13%) were males. The mean age was 41.95 (SD 15.34) years. Only 30 (19.35%) patients had the critical condition. Fever (84.52%) was the most common symptoms, and short of breath was more common in severe patients (p < 0.01). Lymphopenia was observed in most patients (74, 47.7%). It showed the elevation of CRP in 100 (64.5%) patients, the elevation of SAA or IL-6 in 104 (67.1%) patients. The calculated cut-off value of CRP was 19.35 mg/ml, the AUC was 0.777, sensitivity was 73.3%, specificity was 69.6%; SAA was 73.55 mg/L, 0.679, 83.3%, 56.8%, respectively; IL-6 was 18.85 pg/ml, 0.797, 83.3%, 64.8%; D-Dimer was 0.325 mg/L, 0.673, 66.7% and 68.8%. The combination of CRP, SAA, IL-6, and D-Dimer was 0.823 in AUC, 73.3% in sensitivity, and 78.4% in specificity. 12 (42.86%) followed-up patients had completely normal lung function indicators. CONCLUSION: Elevated CRP, SAA, IL-6 and D-Dimer can be predictors to severe COVID-19. The combination of these four indicators can improve the effectivity and specificity of assessing severe COVID-19. Most of the followed-up patients showed no abnormalities in lung function test. Abnormal lung function is mainly reflected in the diffusion function.

EMAP and EMAGE: a framework for understanding spatially organized data.

The Edinburgh MouseAtlas Project (EMAP) is a time-series of mouse-embryo volumetric models. The models provide a context-free spatial framework onto which structural interpretations and experimental data can be mapped. This enables collation, comparison, and query of complex spatial patterns with respect to each other and with respect to known or hypothesized structure. The atlas also includes a time-dependent anatomical ontology and mapping between the ontology and the spatial models in the form of delineated anatomical regions or tissues. The models provide a natural, graphical context for browsing and visualizing complex data. The Edinburgh Mouse Atlas Gene-Expression Database (EMAGE) is one of the first applications of the EMAP framework and provides a spatially mapped gene-expression database with associated tools for data mapping, submission, and query. In this article, we describe the underlying principles of the Atlas and the gene-expression database, and provide a practical introduction to the use of the EMAP and EMAGE tools, including use of new techniques for whole body gene-expression data capture and mapping.

EMAGE: Electronic Mouse Atlas of Gene Expression.

The EMAGE (Electronic Mouse Atlas of Gene Expression) database (http://www.emouseatlas.org/emage) allows users to perform on-line queries of mouse developmental gene expression. EMAGE data are represented spatially using a framework of 3D mouse embryo models, thus allowing uniquely spatial queries to be carried out alongside more traditional text-based queries. This spatial representation of the data also allows a comparison of spatial similarity between the expression patterns. The data are mapped to the models by a team of curators using bespoke mapping software, and the associated meta-data are curated for accuracy and completeness. The data contained in EMAGE are gathered from three main sources: from the published literature, through large-scale screens and collaborations, and via direct submissions from researchers. There are a variety of ways to query the EMAGE database via the on-line search interfaces, as well as via direct computational script-based queries. EMAGE is a free, on-line, community resource funded by the Medical Research Council, UK.