Fast Knowledge Graph Completion using Graphics Processing Units

Knowledge graphs can be used in many areas related to data semantics such as question-answering systems, knowledge based systems. However, the currently constructed knowledge graphs need to be complemented for better knowledge in terms of relations. It is called knowledge graph completion. To add new relations to the existing knowledge graph by using knowledge graph embedding models, we have to evaluate $N\times N \times R$ vector operations, where $N$ is the number of entities and $R$ is the number of relation types. It is very costly. In this paper, we provide an efficient knowledge graph completion framework on GPUs to get new relations using knowledge graph embedding vectors. In the proposed framework, we first define "transformable to a metric space" and then provide a method to transform the knowledge graph completion problem into the similarity join problem for a model which is "transformable to a metric space". After that, to efficiently process the similarity join problem, we derive formulas using the properties of a metric space. Based on the formulas, we develop a fast knowledge graph completion algorithm. Finally, we experimentally show that our framework can efficiently process the knowledge graph completion problem

EzMAP: Easy Microbiome Analysis Platform

Background The rapid advances in next-generation sequencing technologies have revolutionized the microbiome research by greatly increasing our ability to understand diversity of microbes in a given sample. Over the past decade, several computational pipelines have been developed to efficiently process and annotate these microbiome data. However, most of these pipelines require an implementation of additional tools for downstream analyses as well as advanced programming skills. Results Here we introduce a user-friendly microbiome analysis platform, EzMAP (Easy Microbiome Analysis Platform), which was developed using Java Swings, Java Script and R programming language. EzMAP is a standalone package providing graphical user interface, enabling easy access to all the functionalities of QIIME2 (Quantitative Insights Into Microbial Ecology) as well as streamlined downstream analyses using QIIME2 output as input. This platform is designed to give users the detailed reports and the intermediate output files that are generated progressively. The users are allowed to download the features/OTU table (.biom;.tsv;.xls), representative sequences (.fasta) and phylogenetic tree (.nwk), taxonomy assignment file (optional). For downstream analyses, users are allowed to perform relative abundances (at all taxonomical levels), community comparison (alpha and beta diversity, core microbiome), differential abundances (DESeq2 and linear discriminant analysis) and functional prediction (PICRust, Tax4Fun and FunGuilds). Our case study using a published rice microbiome dataset demonstrates intuitive user interface and great accessibility of the EzMAP. Conclusions This EzMAP allows users to consolidate the microbiome analysis processes from raw sequence processing to downstream analyses specific for individual projects. We believe that this will be an invaluable tool for the beginners in their microbiome data analysis. This platform is freely available at https://github.com/gnanibioinfo/EzMAP and will be continually updated for adoption of changes in methods and approaches.This work was supported by grants from Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, and Forestry through Agricultural Microbiome R&D Program, funded by Ministry of Agriculture, Food, and Rural Afairs (MAFRA) (918017–04), by a grant from Rural Development Administration (PJ013178), and by a grant from National Research Foundation of Korea (NRF-2018R1A5A1023599). The funding bodies were not involved in the design of EzMAP and, analysis of data, and in writing the manuscript

Endoscopic Submucosal Dissection of Gastric Epithelial Neoplasms after Partial Gastrectomy: A Single-Center Experience

Aims. To investigate the feasibility and safety of endoscopic submucosal dissection (ESD) of gastric epithelial neoplasms in the remnant stomach (GEN-RS) after various types of partial gastrectomy. Methods. This study included 29 patients (31 lesions) who underwent ESD for GEN-RS between March 2006 and August 2016. Clinicopathologic data were retrieved retrospectively to assess the therapeutic ESD outcomes, including en bloc and complete resection rates and procedure-related adverse events. Results. The en bloc, complete, and curative resection rates were 90%, 77%, and 71%, respectively. The types of previous gastrectomy, tumor size, macroscopic type, and tumor histology were not associated with incomplete resection. Only tumors involving the suture lines from the prior partial gastrectomy were significantly associated with incomplete resection. The procedure-related bleeding and perforation rates were 6% and 3%, respectively; none of the adverse events required surgical intervention. During a median follow-up period of 25 months (range, 6–58 months), there was no recurrence in any case. Conclusions. ESD is a safe and feasible treatment for GEN-RS regardless of the previous gastrectomy type. However, the complete resection rate decreases for lesions involving the suture lines

Transplantation of Adipose Derived Stromal Cells into the Developing Mouse Eye

Adipose derived stromal cells (ADSCs) were transplanted into a developing mouse eye to investigate the influence of a developing host micro environment on integration and differentiation. Green fluorescent protein-expressing ADSCs were transplanted by intraocular injections. The age of the mouse was in the range of 1 to 10 days postnatal (PN). Survival dates ranged from 7 to 28 post transplantation (DPT), at which time immunohistochemistry was performed. The transplanted ADSCs displayed some morphological differentiations in the host eye. Some cells expressed microtubule associated protein 2 (marker for mature neuron), or glial fibrillary acid protein (marker for glial cell). In addition, some cells integrated into the ganglion cell layer. The integration and differentiation of the transplanted ADSCs in the 5 and 10 PN 7 DPT were better than in the host eye the other age ranges. This study was aimed at demonstrating how the age of host micro environment would influence the differentiation and integration of the transplanted ADSCs. However, it was found that the integration and differentiation into the developing retina were very limited when compared with other stem cells, such as murine brain progenitor cell