Resource Ontology Research Articles

Modelling of Resources and Activity of the Scrap Iron and Steel Reverse Supply Chain Service Based on Ontology

Scrap steel reverse supply chain service system is a typical complex system. The realization of the service activities involves a large number of service resources. And there are multiple relationships between atomic service activities and service resources. To realize the search matching between complex service resources and service activity demand in scrap steel reverse supply chain service, the modelling method of service resource information in scrap steel reverse supply chain based on ontology is proposed. After analysing the classification method of service resource, the ontology information model of service resources and service activities is constructed. Then the search matching between service demander and service resource provider is transformed into the mapping between service resource ontology and service activity ontology to solve. Finally, the ontology model of specific instance is established, and the Semantic Web ontology language OWL is used. The model is proved to be correct and feasible by describing the instance service resource ontology and service activity ontology.

The Gene Ontology resource: enriching a GOld mine.

The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations.

Differences in plasma proteomes for active tuberculosis, latent tuberculosis and non-tuberculosis mycobacterial lung disease patients with and without ESAT-6/CFP10 stimulation

BackgroundTuberculosis (TB) is one of the world’s most problematic infectious diseases. The pathogen Mycobacterium tuberculosis (Mtb) is contained by the immune system in people with latent TB infection (LTBI). No overt disease symptoms occur. The environmental and internal triggers leading to reactivation of TB are not well understood. Non-tuberculosis Mycobacteria (NTM) can also cause TB-like lung disease. Comparative analysis of blood plasma proteomes from subjects afflicted by these pathologies in an endemic setting may yield new differentiating biomarkers and insights into inflammatory and immunological responses to Mtb and NTM.MethodsBlood samples from 40 human subjects in a pastoral region of Ethiopia were treated with the ESAT-6/CFP-10 antigen cocktail to stimulate anti-Mtb and anti-NTM immune responses. In addition to those of active TB, LTBI, and NTM cohorts, samples from matched healthy control (HC) subjects were available. Following the generation of sample pools, proteomes were analyzed via LC-MS/MS. These experiments were also performed without antigen stimulation steps. Statistically significant differences using the Z-score method were determined and interpreted in the context of the proteins’ functions and their contributions to biological pathways.ResultsMore than 200 proteins were identified from unstimulated and stimulated plasma samples (UPSs and SPSs, respectively). Thirty-four and 64 proteins were differentially abundant with statistical significance (P < 0.05; Benjamini-Hochberg correction with an FDR < 0.05) comparing UPS and SPS proteomic data of four groups, respectively. Bioinformatics analysis of such proteins via the Gene Ontology Resource was indicative of changes in cellular and metabolic processes, responses to stimuli, and biological regulations. The m7GpppN-mRNA hydrolase was increased in abundance in the LTBI group compared to HC subjects. Charged multivesicular body protein 4a and platelet factor-4 were increased in abundance in NTM as compared to HC and decreased in abundance in NTM as compared to active TB. C-reactive protein, α-1-acid glycoprotein 1, sialic acid-binding Ig-like lectin 16, and vitamin K-dependent protein S were also increased (P < 0.05; fold changes≥2) in SPSs and UPSs comparing active TB with LTBI and NTM cases. These three proteins, connected in a STRING functional network, contribute to the acute phase response and influence blood coagulation.ConclusionPlasma proteomes are different comparing LTBI, TB, NTM and HC cohorts. The changes are augmented following prior blood immune cell stimulation with the ESAT-6/CFP-10 antigen cocktail. The results encourage larger-cohort studies to identify specific biomarkers to diagnose NTM infection, LTBI, and to predict the risk of TB reactivation.

Laryngeal Squamous Cell Carcinoma: Potential Molecular Mechanism and Prognostic Signature Based on Immune-Related Genes.

BackgroundImmune-related genes (IRGs) are closely related to the incidence and progression of tumors, potentially indicating that IRGs play an important role in laryngeal squamous cell carcinoma (LSCC).Material/MethodsAn RNA sequencing dataset containing 123 samples was collected from The Cancer Genome Atlas. Based on immune-related differentially expressed genes (IRDEGs), a potential molecular mechanism of LSCC was explored through analysis of information in the Gene Ontology (GO) resource and the Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interactions (PPIs). A regulatory network of transcriptional regulators and IRDEGs was constructed to explore the underlying molecular mechanism of LSCC at the upstream level. Candidates from IRDEGs for signature were screened via univariate Cox analysis and using the least absolute shrinkage and selection operator (LASSO) technique. The IRDEG signature of LSCC was constructed by using a multivariate Cox proportional hazards model.ResultsGO and KEGG analysis showed that IRDEGs may participate in the progression of LSCC through immune-related reactions. PPI analysis demonstrated that, among the IRDEGs in LSCC, the Kininogen 1; C-X-X motif chemokine ligand 10; elastase, neutrophil expressed; and LYZ genes are hub genes in the development of LSCC. At the upstream level, SPI1, SP140, signal transducer and activator of transcription 4, zinc finger E-box binding homeobox, and Ikaros family zinc finger 2 are the hub transcriptional regulators of IRDEGs. The risk score based on the IRDEG signature was able to distinguish prognosis in patients with LSCC and represents an independent prognostic risk factor for LSCC.ConclusionsFrom the perspective of IRGs, we first constructed an IRDEG signature related to the prognosis of LSCC, which can be used as a novel marker to predict prognosis in patients with LSCC.

Bioinformatics analysis of LINC01554 and its co‑expressed genes in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related morbidity and mortality globally. Despite the remarkable improvements in comprehensive HCC treatment, the underlying mechanistic details of HCC remain elusive. We screened HCC patients for differentially expressed genes (DEGs) using the Gene Expression Omnibus (GSE113850) and The Cancer Genome Atlas (TCGA) datasets. LINC01554 expression in 40 paired samples was determined by quantitative reverse transcription polymerase chain reaction (RT-qPCR), and its clinical significance was assessed. LINC01554 was found to have a gain-of-function role in HCC in vitro. Additionally, the bioinformatics analysis of the genes co-expressed with LINC01554 was performed using the Co-LncRNA website, and potential molecular mechanisms were investigated using the Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes resources and validated by in vitro experiments. A total of 229 DEGs were identified from the GSE113850 dataset. Among the identified DEGs, three long non-coding RNAs (lncRNAs) (DIO3OS, LINC01554, and LINC01093) with |logFC| ≥2 and P<0.05 were screened. A total of 148 lncRNAs with |logFC| ≥1 and P<0.05 were identified from TCGA dataset. Low LINC01554 expression levels were significantly correlated with overall survival, pathological stage, hepatitis B infection, tumour size, portal vein tumour thrombus, and TNM stage. Using gain-of-function assays, we further showed that LINC01554 inhibited the proliferation, migration, and invasion of the HCCLM9 and SK-Hep1 cells and promoted G0/G1 arrest, but it did not significantly affect apoptosis. Western blotting revealed that LINC01554 overexpression resulted in increased ZO-1 and E-cadherin expression levels, but decreased N-cadherin and vimentin expression levels. Moreover, LINC01554 overexpression inhibited Akt, p-Akt, β-catenin, and p-Gsk3β expression. Our results showed that LINC01554 repressed HCC cell invasiveness and epithelial-to-mesenchymal transition partly by inhibiting Wnt and PI3K-Akt signalling in vitro. Taken together, our findings provide new insights into the molecular mechanisms underlying HCC tumourigenesis and implicate LINC01554 as a potential target for HCC therapy.

Cytokines mapping for tissue-specific expression, eQTLs and GWAS traits

Dysregulation in cytokine production has been linked to the pathogenesis of various immune-mediated traits, in which genetic variability contributes to the etiopathogenesis. GWA studies have identified many genetic variants in or near cytokine genes, nonetheless, the translation of these findings into knowledge of functional determinants of complex traits remains a fundamental challenge. In this study we aimed at collection, analysis and interpretation of data on cytokines focused on their tissue-specific expression, eQTLs and GWAS traits. Using GO annotations, we generated a list of 314 cytokines and analyzed them with the GTEx resource. Cytokines were highly tissue-specific, 82.3% of cytokines had Tau expression metrics ≥ 0.8. In total, 3077 associations for 1760 unique SNPs in or near 244 cytokines were mapped in the NHGRI-EBI GWAS Catalog. According to the Experimental Factor Ontology resource, the largest numbers of disease associations were related to ‘Inflammatory disease’, ‘Immune system disease’ and ‘Asthma’. The GTEx-based analysis revealed that among GWAS SNPs, 1142 SNPs had eQTL effects and influenced expression levels of 999 eGenes, among them 178 cytokines. Several types of enrichment analysis showed that it was cytokines expression variability that fundamentally contributed to the molecular origins of considered immune-mediated conditions.

Identification of potential crucial genes in atrial fibrillation: a bioinformatic analysis

BackgroundAtrial fibrillation (AF) is at least partially heritable, affecting 2–3% of the population in Europe and the USA. However, a substantial proportion of heritability is still lacking. In the present study, we aim to identify potential crucial genes associated with AF through bioinformatic analyses of public datasets.MethodsMicroarray data sets of GSE115574, GSE31821, GSE79768, GSE41177 and GSE14975 from the Gene Expression Omnibus (GEO) database were retrieved. After merging all microarray data and adjusting batch effect, differentially expressed genes (DEGs) were identified. Functional enrichment analyses based on Gene Ontology (GO) resource, Kyoto Encyclopedia of Genes and Genomes (KEGG) resource, Gene Set Enrichment Analysis (GSEA), Reactome Pathway Database and Disease Ontology (DO) were carried out. Protein-protein interaction (PPI) network was constructed using the STRING database. Combined with aforementioned significant bioinformatics information, potential crucial genes were subsequently selected. The comparative toxicogenomics database (CTD) was used to explore the interaction between potential crucial genes and AF.ResultWe identified 27 of DEGs with gene expression fold change (FC) ≥ 1.5 or ≤ 2/3 (|log2 FC| ≥ 0.58) and 5 with FC ≥ 2 or ≤ 0.5 (|log2 FC| ≥ 1) of AF patients compared with sinus rhythm controls. The most significantly enriched pathway was regulation of insulin-like growth factor transport and uptake by insulin-like growth factor binding proteins. IGFBP2, C1orf105, FHL2, CHGB, ATP1B4, IGFBP3, SLC26A9, CXCR4 and HTR2B were considered the potential crucial genes. CTD showed CXCR4, IGFBP2, IGFBP3 and FHL2 had higher scores with AF.ConclusionsThe 9 potential crucial genes, especially CXCR4, IGFBP2, IGFBP3 and FHL2, may be associated with risk of AF. Our study provided new insights of AF into genetics, molecular pathogenesis and new therapeutic targets.

Weaving people and places: Landscapes of obsidian circulation in NW Argentina. A long-term view (ca. CE 100–1436)

Ancient exchange practices have long been at the centre of comparative studies of social complexity. While finding valuable information, this approach has paid less attention to the multi-layered cultural understandings underpinning past transactions, ultimately diluting the power of archaeology to understand specific historical trajectories. This article examines the circulation and uses of obsidian in two sectors of the Calchaquí Valleys area of northwestern Argentina, considering contextual information from Early to Late Period (ca. CE 100–1436) settlements. Travelling far and widely, obsidian wove people and places in space and time through material interactions, condensing the broader regional world into partible materials for everyday use. While maintaining a generalised access ethos throughout the sequence, obsidian also enabled new forms of communal organisation and leadership. The article contributes to wider interdisciplinary approaches to the ontology of resources and their transformative social power, both in the Andes and beyond.

A Semantic Focused Web Crawler Based on a Knowledge Representation Schema

The Web has become the main source of information in the digital world, expanding to heterogeneous domains and continuously growing. By means of a search engine, users can systematically search over the web for particular information based on a text query, on the basis of a domain-unaware web search tool that maintains real-time information. One type of web search tool is the semantic focused web crawler (SFWC); it exploits the semantics of the Web based on some ontology heuristics to determine which web pages belong to the domain defined by the query. An SFWC is highly dependent on the ontological resource, which is created by domain human experts. This work presents a novel SFWC based on a generic knowledge representation schema to model the crawler’s domain, thus reducing the complexity and cost of constructing a more formal representation as the case when using ontologies. Furthermore, a similarity measure based on the combination of the inverse document frequency (IDF) metric, standard deviation, and the arithmetic mean is proposed for the SFWC. This measure filters web page contents in accordance with the domain of interest during the crawling task. A set of experiments were run over the domains of computer science, politics, and diabetes to validate and evaluate the proposed novel crawler. The quantitative (harvest ratio) and qualitative (Fleiss’ kappa) evaluations demonstrate the suitability of the proposed SFWC to crawl the Web using a knowledge representation schema instead of a domain ontology.

Seeking Windows of Opportunity to Shape Lifelong Immune Health: A Network-Based Strategy to Predict and Prioritize Markers of Early Life Immune Modulation.

A healthy immune status is strongly conditioned during early life stages. Insights into the molecular drivers of early life immune development and function are prerequisite to identify strategies to enhance immune health. Even though several starting points for targeted immune modulation have been identified and are being developed into prophylactic or therapeutic approaches, there is no regulatory guidance on how to assess the risk and benefit balance of such interventions. Six early life immune causal networks, each compromising a different time period in early life (the 1st, 2nd, 3rd trimester of gestations, birth, newborn, and infant period), were generated. Thereto information was extracted and structured from early life literature using the automated text mining and machine learning tool: Integrated Network and Dynamical Reasoning Assembler (INDRA). The tool identified relevant entities (e.g., genes/proteins/metabolites/processes/diseases), extracted causal relationships among these entities, and assembled them into early life-immune causal networks. These causal early life immune networks were denoised using GeneMania, enriched with data from the gene-disease association database DisGeNET and Gene Ontology resource tools (GO/GO-SLIM), inferred missing relationships and added expert knowledge to generate information-dense early life immune networks. Analysis of the six early life immune networks by PageRank, not only confirmed the central role of the “commonly used immune markers” (e.g., chemokines, interleukins, IFN, TNF, TGFB, and other immune activation regulators (e.g., CD55, FOXP3, GATA3, CD79A, C4BPA), but also identified less obvious candidates (e.g., CYP1A2, FOXK2, NELFCD, RENBP). Comparison of the different early life periods resulted in the prediction of 11 key early life genes overlapping all early life periods (TNF, IL6, IL10, CD4, FOXP3, IL4, NELFCD, CD79A, IL5, RENBP, and IFNG), and also genes that were only described in certain early life period(s). Concluding, here we describe a network-based approach that provides a science-based and systematical method to explore the functional development of the early life immune system through time. This systems approach aids the generation of a testing strategy for the safety and efficacy of early life immune modulation by predicting the key candidate markers during different phases of early life immune development.

Exhausted phenotype of follicular CD8 T cells in CVID

Exhausted phenotype of follicular CD8 T cells in CVID

A Parsons Tale: Tractarian Reflections on a Semantical Paradox

AbstractAccording to Charles Parsons, a liar sentence does not express a proposition at the level of its primary use but does at the level where it is subjected to semantic interpretation. Thus, richer ontological resources unavailable at the level of primary use are available at the level of interpretation. In response to the objection that the correct semantic interpretation of a liar sentence is thereby distorted, I explain how Wittgenstein’s repudiation of “logical objects” and the Tractarian notion of an intrinsically iterative operation show that the liar sentence’s primary use anticipates but does not presuppose the richer interpretive ontology.

Question Answering Systems on Holy Quran: A Review of Existing Frameworks, Approaches, Algorithms and Research Issues

Question Answering System has the ability to present an answer based on a question submitted by the user in natural languages. This system consists of question processing, document retrieval, and answer extraction component. Challenge to optimize Question Answering’s system is to increase the performance of all components in the framework. The performance of all component which has not been optimized has caused to the lack of accurate answer from the systems. Based on this issue, the purpose of this research is to investigate the research gaps in the current state of existing Question Answering Systems on Holy Quran. The result of this study reveals potential research issues, namely morphology analysis, question classification, search techniques, and ontology resources.

Complete Genome Insights into Lactococcus petauri CF11 Isolated from a Healthy Human Gut Using Second- and Third-Generation Sequencing.

Lactococcus petauri CF11 was originally isolated from the gut of healthy humans. To determine the underlying molecular and genetic mechanisms of the probiotic potential of CF11, we performed complete genome sequencing, annotation, and comparative genome analysis. The complete genome of L. petauri CF11 comprised of 1,997,720 bp, with a DNA G+C content of 38.21 mol% containing 1982 protein coding genes and 16 rRNA operons. We found that 1206 genes (56.05%) were assigned a putative function using the gene ontology (GO) resource. The gene products of CF11 were primarily concentrated in molecular function and biological processes, such as catalysis, binding, metabolism, and cellular processes. Furthermore, 1,365 (68.87%) genes were assigned an illative function using COGs. CF11 proteins were associated with carbohydrate transport and metabolism, and amino acid transport and metabolism. This indicates that CF11 bacteria can perform active energy exchange. We classified 1,111 (56.05%) genes into six KEGG functional categories; fructose-bisphosphate aldolase and the phosphoenol pyruvate:phosphotransferase system (PTS), which are necessary in producing short-chain fatty acids (SCFAs), were excited in the carbohydrate metabolic pathway. This suggests that L. petauri CF11 produces SCFAs via glycolysis. The genomic island revealed that some regions contain fragments of antibiotic resistance and bacteriostatic genes. In addition, ANI analysis showed that L. petauri CF11 had the closest relationship with L. petauri 159469T, with an average nucleotide consistency of 98.03%. Taken together, the present study offers further insights into the functional and potential role of L. petauri CF11 in health care.

Bidirectional Transformation of MES Source Code and Ontologies

Future production environments must be flexible and reconfigurable. To achieve this, the devices and services to fulfill the different steps of a production order (PO) should not be selected in the manufacturing execution system (MES), but in an edge component close to the shop floor. To enable this, abstract services in the PO and concrete services provided by the field devices on the shop floor need to refer to a production ontology. The creation of this ontology is a challenge of its own. This research proposes a pragmatic automation of an encoding of a primary and light weight production ontology based on the source code of MES. The transformation procedure of source code to resource, product and generic concepts of the manufacturing plant ontology is described. To this end, the knowledge of OPC UA collaborations are also exploited during the creation of resource ontologies. Due to a fundamental difference between source code implementation (imperative paradigm) and ontology representation (declarative paradigm), the problem of information loss is inevitable. This problem is overcome by formulation of production and business rules that encapsulate the logic of the MES. The foundation of ontology is exploited to formulate these rulesets using OWL based constructs and OWL based rule languages such as Semantic Web Rule Language (SWRL), Semantic Query-Enhanced Web Rule Language (SQWRL) and SPARQL Protocol and RDF Query Language (SPARQL) based on feasibility and requirements of specific rules. Further, these rulesets are either run on the automatically generated ontology at design time with an intention to enrich the knowledge base, or production runtime to validate the pre-defined business rules between the production steps. The generated ontology also acts as basis for automatically generating the OWL-S ontologies for the OPC UA application methods for the purpose of dynamic manufacturing service discovery and orchestration. The generated ontology and an abstract PO hooked with formulated rules are cached to the shop-floor network for consequent production control to enable smart edge production. An implementation is conducted on an industrial use-case demonstrator to evaluate the applicability of the proposed approach.

An Ontology Based Expert System for Lung Cancer : OBESLC

Lung Cancer is the second most recurrent cancer in both men and women and which is the leading cause of cancer death worldwide. The American cancer Society (ACS) in US estimates nearly 228,150 new cases of lung cancer and 142,670 deaths from lung cancer for the year 2019. This paper proposes to build an ontology based expert system to diagnose Lung Cancer Disease and to identify the stage of Lung Cancer. Ontology is defined as a specification of conceptualization and describes knowledge about any domain in the form of concepts and relationships among them. It is a framework for representing shareable and reusable knowledge across a domain. The advantage of using ontology for knowledge representation of a particular domain is they are machine readable. We designed a System named OBESLC (Ontology Based Expert System for Lung Cancer) for lung cancer diagnosis, in that to construct an ontology we make use of Ontology Web Language (OWL) and Resource Description Framework (RDF) .The design of this system depends on knowledge about patient’s symptoms and the state of lung nodules to build knowledge base of Lung Cancer Disease. We verified our ontology OBESLC by querying it using SPARQL query language, a popular query language for extracting required information from Semantic web. We validate our ontology by developing reasoning rules using semantic Web Rule Language (SWRL).To provide the user interface, we implemented our approach in java using Jena API and Eclipse Editor.

Radiant: understanding endometrial cancer, vaginal brachytherapy and motherhood through words and images

Este artigo resulta de uma análise antropológica centrada na experiência do diagnóstico e tratamento de um adenocarcinoma do endométrio vivida por uma mulher portuguesa. A dimensão incorporada do seu conhecimento e narrativa permite-nos compreender um conjunto específico de problemas enfrentados por mulheres com câncer ginecológico, mostrando como concepções de doença, tratamento, corporeidade, sexualidade, maternidade e resistência se interligam. A doença e o seu filho de três anos emergem como dois elementos opostos da história, veiculando a noção de uma resistência construída pela parentalidade, ou pela condição de mãe, usando-se esse vínculo contra as violências e sofrimentos produzidos pelo câncer e seu tratamento. Metodologicamente, esta análise combina narrativa oral, antropologia e ilustração científica criativa, ou seja, pintura e desenho etnográfico potenciados pelo uso da metáfora e da imaginação. Este exercício híbrido e colaborativo implicou uma mistura nivelada de fala, texto e imagem, partindo das palavras da mulher entrevistada. Conceptualmente, estas práticas visuais criativas são entendidas como recursos ontológicos, epistemológicos e performativos, ampliando a forma como a ciência social pode produzir conhecimento e ação em questões de saúde e doença. Lua aceitou contar a sua história preservando a sua identidade sob um pseudónimo, não encontrando abertura social para relatos sobre úteros cancerosos e sessões de braquiterapia vaginal. Respondendo ao seu desconforto, esta análise ilustrada também pretende desmantelar estereótipos enraizados na forma como vemos e entendemos as mulheres, as doenças ginecológicas e os órgãos sexuais, trazendo para a discussão um tipo de câncer que, apesar de frequente, permanece ausente da discussão pública e da imagética coletiva, sendo igualmente descurado pela ciência social.

Research on the technical method of constructing the evaluation system of geological cultural village

The current rural construction presents a new situation in which multiple perspectives are involved. As one of the important cut-in points for intervention, the academic community has begun to explore and practice the rural construction model based on “geological culture”. Starting from the ontology of rural geological environment resources, the four-dimensional attributes including geological relics, agricultural geological resources, human landscapes and natural landscapes are concerned, and the evaluation method of geological culture village based on analytic hierarchy process (AHP) is discussed. Through the comprehensive evaluation index system of geological culture villages with two basic connotations of environmental resources, development conditions and development benefits, seven types of geological relics, agricultural geological resources, human landscape, natural landscape, human settlement environment, public service and development benefit are proposed. The second-level index consists of a total of 16 third-level indicators of the comprehensive evaluation system of geological culture villages. The article aims to lay a foundation for the planning and design of geological and cultural villages through the construction of the evaluation system and promote the healthy and sustainable development of the geological culture villages.

Identification of hub genes and small-molecule compounds related to intracerebral hemorrhage with bioinformatics analysis.

BackgroundBecause of the complex mechanisms of injury, conventional surgical treatment and early blood pressure control does not significantly reduce mortality or improve patient prognosis in cases of intracerebral hemorrhage (ICH). We aimed to identify the hub genes associated with intracerebral hemorrhage, to act as therapeutic targets, and to identify potential small-molecule compounds for treating ICH.MethodsThe GSE24265 dataset, consisting of data from four perihematomal brain tissues and seven contralateral brain tissues, was downloaded from the Gene Expression Omnibus (GEO) database and screened for differentially expressed genes (DEGs) in ICH, with a fold change (FC) value of (|log2FC|) > 2 and a P-value of <0.05 set as cut-offs. The functional annotation of DEGs was performed using Gene Ontology (GO) resources, and the cell signaling pathway analysis of DEGs was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG), with a P-value of <0.05 set as the cut-off. We constructed a protein-protein interaction (PPI) network to clarify the interrelationships between the different DEGs and to select the hub genes with significant interactions. Next, the DEGs were analyzed using the CMap tool to identify small-molecule compounds with potential therapeutic effects. Finally, we verified the expression levels of the hub genes by RT-qPCR on the rat ICH model.ResultA total of 59 up-regulated genes and eight down-regulated genes associated with ICH were identified. The biological functions of DEGs associated with ICH are mainly involved in the inflammatory response, chemokine activity, and immune response. The KEGG analysis identified several pathways significantly associated with ICH, including but not limited to HIF-1, TNF, toll-like receptor, cytokine-cytokine receptor interaction, and chemokine molecules. A PPI network consisting of 57 nodes and 373 edges was constructed using STRING, and 10 hub genes were identified with Cytoscape software. These hub genes are closely related to secondary brain injury induced by ICH. RT-qPCR results showed that the expression of ten hub genes was significantly increased in the rat model of ICH. In addition, a CMap analysis of three small-molecule compounds revealed their therapeutic potential.ConclusionIn this study we obtained ten hub genes, such as IL6, TLR2, CXCL1, TIMP1, PLAUR, SERPINE1, SELE, CCL4, CCL20, and CD163, which play an important role in the pathology of ICH. At the same time, the ten hub genes obtained through PPI network analysis were verified in the rat model of ICH. In addition, we obtained three small molecule compounds that will have therapeutic effects on ICH, including Hecogenin, Lidocaine, and NU-1025.

Aggregating the syntactic and semantic similarity of healthcare data towards their transformation to HL7 FHIR through ontology matching

Background and objectiveHealthcare systems deal with multiple challenges in releasing information from data silos, finding it almost impossible to be implemented, maintained and upgraded, with difficulties ranging in the technical, security and human interaction fields. Currently, the increasing availability of health data is demanding data-driven approaches, bringing the opportunities to automate healthcare related tasks, providing better disease detection, more accurate prognosis, faster clinical research advance and better fit for patient management. In order to share data with as many stakeholders as possible, interoperability is the only sustainable way for letting systems to talk with one another and getting the complete image of a patient. Thus, it becomes clear that an efficient solution in the data exchange incompatibility is of extreme importance. Consequently, interoperability can develop a communication framework between non-communicable systems, which can be achieved through transforming healthcare data into ontologies. However, the multidimensionality of healthcare domain and the way that is conceptualized, results in the creation of different ontologies with contradicting or overlapping parts. Thus, an effective solution to this problem is the development of methods for finding matches among the various components of ontologies in healthcare, in order to facilitate semantic interoperability. MethodsThe proposed mechanism promises healthcare interoperability through the transformation of healthcare data into the corresponding HL7 FHIR structure. In more detail, it aims at building ontologies of healthcare data, which are later stored into a triplestore. Afterwards, for each constructed ontology the syntactic and semantic similarities with the various HL7 FHIR Resources ontologies are calculated, based on their Levenshtein distance and their semantic fingerprints accordingly. Henceforth, after the aggregation of these results, the matching to the HL7 FHIR Resources takes place, translating the healthcare data into a widely adopted medical standard. ResultsThrough the derived results it can be seen that there exist cases that an ontology has been matched to a specific HL7 FHIR Resource due to its syntactic similarity, whereas the same ontology has been matched to a different HL7 FHIR Resource due to its semantic similarity. Nevertheless, the developed mechanism performed well since its matching results had exact match with the manual ontology matching results, which are considered as a reference value of high quality and accuracy. Moreover, in order to furtherly investigate the quality of the developed mechanism, it was also evaluated through its comparison with the Alignment API, as well as the non-dominated sorting genetic algorithm (NSGA-III) which provide ontology alignment. In both cases, the results of all the different implementations were almost identical, proving the developed mechanism’s high efficiency, whereas through the comparison with the NSGA-III algorithm, it was observed that the developed mechanism needs additional improvements, through a potential adoption of the NSGA-III technique. ConclusionsThe developed mechanism creates new opportunities in conquering the field of healthcare interoperability. However, according to the mechanism’s evaluation results, it is almost impossible to create syntactic or semantic patterns for understanding the nature of a healthcare dataset. Hence, additional work should be performed in evaluating the developed mechanism, and updating it with respect to the results that will derive from its comparison with similar ontology matching mechanisms and data of multiple nature.