Cytokine and molecular networks in sepsis cases: a network biology approach View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-09

AUTHORS

Dong Wook Jekarl, Kyung Soo Kim, Seungok Lee, Myungshin Kim, Yonggoo Kim

ABSTRACT

Sepsis is a life-threatening condition of organ dysfunction caused by a dysregulated host immune response to infection. We performed network analysis of cytokine molecules and compared network structures between a systematic inflammatory response syndrome (SIRS) or normal control (NC) group and a sepsis group. We recruited SIRS (n = 33) and sepsis (n = 89) patients from electronic medical records (EMR) according to whether data on PCT, CRP, interleukin (IL)-1β, IL-2, IL-4, IL-5, IL-6, IL-9, IL-10, IL-12p70, IL-13, IL-17, IL-22, TNF-α, and IFN-γ levels were available. From the public GEO dataset, GSE66099, GSE9960, GSE95233, GSE57065 were downloaded. Genes corresponding to 15 molecules were extracted from an expression array. A correlation matrix was formed for the 15 molecules and statistically significant molecular pairs were used as pairs for network analysis of coexpression. The number of molecular or gene expression pairs significantly correlated among the SIRS or control and sepsis groups are as follows for datasets: EMR, 15 and 15; GEO66099-1, 13 and 15; GEO9960, 13 and 11; GSE95233, 13 and 8; GSE66099-2, 15 and 14; GSE57065, 14 and 13, respectively. Network analysis revealed that network diameter, number of nodes and shortest path were equal to or lower in the sepsis group. The coexpression network in sepsis patients was relatively small sized and had lower shortest paths compared with the SIRS group or healthy control group. Cytokines with one degree (k = 1) are increased in sepsis group compared with SIRS or healthy control group. IL-9 and IL-2 were not included in network of sepsis group indicating that these cytokines showed no correlation with other cytokines. These data might imply that cytokines tend to be dysregulated in the sepsis group compared to that of SIRS or normal control groups. More... »

PAGES

103-111

Identifiers

URI

http://scigraph.springernature.com/pub.10.1684/ecn.2018.0414

DOI

http://dx.doi.org/10.1684/ecn.2018.0414

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1111024058

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30547887


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1107", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Immunology", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Adult", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Child", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Child, Preschool", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Cytokines", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Databases, Factual", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Infant", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Male", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Retrospective Studies", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Sepsis", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Catholic University of Korea", 
          "id": "https://www.grid.ac/institutes/grid.411947.e", 
          "name": [
            "Department of Laboratory Medicine, Incheon St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea", 
            "Laboratory for Development and Evaluation Center, Seoul St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Jekarl", 
        "givenName": "Dong Wook", 
        "id": "sg:person.0630010543.71", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0630010543.71"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Catholic University of Korea", 
          "id": "https://www.grid.ac/institutes/grid.411947.e", 
          "name": [
            "Department of Thoracic and Cardiovascular Surgery, Seoul St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kim", 
        "givenName": "Kyung Soo", 
        "id": "sg:person.0714317030.03", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0714317030.03"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Catholic University of Korea", 
          "id": "https://www.grid.ac/institutes/grid.411947.e", 
          "name": [
            "Department of Laboratory Medicine, Incheon St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea", 
            "Laboratory for Development and Evaluation Center, Seoul St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lee", 
        "givenName": "Seungok", 
        "id": "sg:person.01163541077.61", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01163541077.61"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Catholic University of Korea", 
          "id": "https://www.grid.ac/institutes/grid.411947.e", 
          "name": [
            "Department of Laboratory Medicine, Seoul St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, 06591, Seoul, Republic of Korea", 
            "Laboratory for Development and Evaluation Center, Seoul St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kim", 
        "givenName": "Myungshin", 
        "id": "sg:person.07564035574.49", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07564035574.49"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Catholic University of Korea", 
          "id": "https://www.grid.ac/institutes/grid.411947.e", 
          "name": [
            "Department of Laboratory Medicine, Seoul St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, 06591, Seoul, Republic of Korea", 
            "Laboratory for Development and Evaluation Center, Seoul St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kim", 
        "givenName": "Yonggoo", 
        "id": "sg:person.01352610144.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01352610144.46"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1186/1756-0381-4-10", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002056061", 
          "https://doi.org/10.1186/1756-0381-4-10"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.diagmicrobio.2012.12.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004417402"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/cc5783", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004605172", 
          "https://doi.org/10.1186/cc5783"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1001/jama.2011.1829", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006669572"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1378/chest.101.6.1644", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006971593"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s40635-014-0020-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007337554", 
          "https://doi.org/10.1186/s40635-014-0020-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s40635-014-0020-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007337554", 
          "https://doi.org/10.1186/s40635-014-0020-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1515/cclm-2014-0607", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007773945"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/btm254", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010833586"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0005686", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012755725"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nprot.2012.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015407882", 
          "https://doi.org/10.1038/nprot.2012.004"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1001/jama.2016.0288", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016776662"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1001/jama.2016.0288", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016776662"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrg1272", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018231980", 
          "https://doi.org/10.1038/nrg1272"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrg1272", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018231980", 
          "https://doi.org/10.1038/nrg1272"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmra021333", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019375943"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0028870", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020393737"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrg2918", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021371713", 
          "https://doi.org/10.1038/nrg2918"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrg2918", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021371713", 
          "https://doi.org/10.1038/nrg2918"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/cc10274", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022380816", 
          "https://doi.org/10.1186/cc10274"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jinf.2016.01.010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023580079"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.2212", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026331197", 
          "https://doi.org/10.1038/nmeth.2212"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/cc9392", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030309905", 
          "https://doi.org/10.1186/cc9392"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmra1208623", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032706237"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature01326", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033794061", 
          "https://doi.org/10.1038/nature01326"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature01326", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033794061", 
          "https://doi.org/10.1038/nature01326"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/scitranslmed.aaa5993", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035837481"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2105-10-109", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036359613", 
          "https://doi.org/10.1186/1471-2105-10-109"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2105-10-109", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036359613", 
          "https://doi.org/10.1186/1471-2105-10-109"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2164-15-997", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037805312", 
          "https://doi.org/10.1186/1471-2164-15-997"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmoa1415236", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039137824"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/09680519010070020201", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043958244"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/09680519010070020201", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043958244"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/ccm.0b013e31819b52fd", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045641395"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/ccm.0b013e31819b52fd", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045641395"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1001/jama.2016.0287", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045696843"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/ccm.0b013e318258fb70", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049099601"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/ccm.0b013e318258fb70", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049099601"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gad.1528707", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050597665"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/pmic.201000684", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051849365"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1089/jir.2014.0119", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059281553"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1684/ecn.2011.0281", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1078404380"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.humimm.2017.03.010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084078899"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-09", 
    "datePublishedReg": "2018-09-01", 
    "description": "Sepsis is a life-threatening condition of organ dysfunction caused by a dysregulated host immune response to infection. We performed network analysis of cytokine molecules and compared network structures between a systematic inflammatory response syndrome (SIRS) or normal control (NC) group and a sepsis group. We recruited SIRS (n\u2009=\u200933) and sepsis (n\u2009=\u200989) patients from electronic medical records (EMR) according to whether data on PCT, CRP, interleukin (IL)-1\u03b2, IL-2, IL-4, IL-5, IL-6, IL-9, IL-10, IL-12p70, IL-13, IL-17, IL-22, TNF-\u03b1, and IFN-\u03b3 levels were available. From the public GEO dataset, GSE66099, GSE9960, GSE95233, GSE57065 were downloaded. Genes corresponding to 15 molecules were extracted from an expression array. A correlation matrix was formed for the 15 molecules and statistically significant molecular pairs were used as pairs for network analysis of coexpression. The number of molecular or gene expression pairs significantly correlated among the SIRS or control and sepsis groups are as follows for datasets: EMR, 15 and 15; GEO66099-1, 13 and 15; GEO9960, 13 and 11; GSE95233, 13 and 8; GSE66099-2, 15 and 14; GSE57065, 14 and 13, respectively. Network analysis revealed that network diameter, number of nodes and shortest path were equal to or lower in the sepsis group. The coexpression network in sepsis patients was relatively small sized and had lower shortest paths compared with the SIRS group or healthy control group. Cytokines with one degree (k\u2009=\u20091) are increased in sepsis group compared with SIRS or healthy control group. IL-9 and IL-2 were not included in network of sepsis group indicating that these cytokines showed no correlation with other cytokines. These data might imply that cytokines tend to be dysregulated in the sepsis group compared to that of SIRS or normal control groups.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1684/ecn.2018.0414", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1100922", 
        "issn": [
          "1148-5493", 
          "1952-4005"
        ], 
        "name": "European Cytokine Network", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "3", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "29"
      }
    ], 
    "name": "Cytokine and molecular networks in sepsis cases: a network biology approach", 
    "pagination": "103-111", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "d10f4fd679978e1a34cfe08042dc7bbe75a546aef481b387fcefb0a4f6e4e461"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30547887"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "9100879"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1684/ecn.2018.0414"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1111024058"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1684/ecn.2018.0414", 
      "https://app.dimensions.ai/details/publication/pub.1111024058"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T13:18", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000368_0000000368/records_78944_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1684%2Fecn.2018.0414"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1684/ecn.2018.0414'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1684/ecn.2018.0414'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1684/ecn.2018.0414'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1684/ecn.2018.0414'


 

This table displays all metadata directly associated to this object as RDF triples.

258 TRIPLES      21 PREDICATES      74 URIs      32 LITERALS      20 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1684/ecn.2018.0414 schema:about N1a5eb2fd6c73481b9fea3e05cbe80ee8
2 N5dd3277c653347369a39a331636aa8dc
3 N6845c347fc2e47f79948b8c0b912b002
4 N70e926bd1599458c90ef35645cc33901
5 N76a9512850ce41669b05bc18fac3f469
6 N8e6d6bc99e664d7e8d7cd0bf042f673d
7 Na2b93186d49e406f8f86119bb3ca52dd
8 Nd7e690c8fd4c4443bba9d979081badfe
9 Nf48af6495e234a949c711507d48b1e70
10 Nf7e404d5f18d4426b3026977d97d1006
11 Nfb636e02a65f4c9fa318f57a9339df0d
12 anzsrc-for:11
13 anzsrc-for:1107
14 schema:author Nba66fde527a541bf8ad7c8f71125f4f9
15 schema:citation sg:pub.10.1038/nature01326
16 sg:pub.10.1038/nmeth.2212
17 sg:pub.10.1038/nprot.2012.004
18 sg:pub.10.1038/nrg1272
19 sg:pub.10.1038/nrg2918
20 sg:pub.10.1186/1471-2105-10-109
21 sg:pub.10.1186/1471-2164-15-997
22 sg:pub.10.1186/1756-0381-4-10
23 sg:pub.10.1186/cc10274
24 sg:pub.10.1186/cc5783
25 sg:pub.10.1186/cc9392
26 sg:pub.10.1186/s40635-014-0020-3
27 https://doi.org/10.1001/jama.2011.1829
28 https://doi.org/10.1001/jama.2016.0287
29 https://doi.org/10.1001/jama.2016.0288
30 https://doi.org/10.1002/pmic.201000684
31 https://doi.org/10.1016/j.diagmicrobio.2012.12.011
32 https://doi.org/10.1016/j.humimm.2017.03.010
33 https://doi.org/10.1016/j.jinf.2016.01.010
34 https://doi.org/10.1056/nejmoa1415236
35 https://doi.org/10.1056/nejmra021333
36 https://doi.org/10.1056/nejmra1208623
37 https://doi.org/10.1089/jir.2014.0119
38 https://doi.org/10.1093/bioinformatics/btm254
39 https://doi.org/10.1097/ccm.0b013e31819b52fd
40 https://doi.org/10.1097/ccm.0b013e318258fb70
41 https://doi.org/10.1101/gad.1528707
42 https://doi.org/10.1126/scitranslmed.aaa5993
43 https://doi.org/10.1177/09680519010070020201
44 https://doi.org/10.1371/journal.pone.0005686
45 https://doi.org/10.1371/journal.pone.0028870
46 https://doi.org/10.1378/chest.101.6.1644
47 https://doi.org/10.1515/cclm-2014-0607
48 https://doi.org/10.1684/ecn.2011.0281
49 schema:datePublished 2018-09
50 schema:datePublishedReg 2018-09-01
51 schema:description Sepsis is a life-threatening condition of organ dysfunction caused by a dysregulated host immune response to infection. We performed network analysis of cytokine molecules and compared network structures between a systematic inflammatory response syndrome (SIRS) or normal control (NC) group and a sepsis group. We recruited SIRS (n = 33) and sepsis (n = 89) patients from electronic medical records (EMR) according to whether data on PCT, CRP, interleukin (IL)-1β, IL-2, IL-4, IL-5, IL-6, IL-9, IL-10, IL-12p70, IL-13, IL-17, IL-22, TNF-α, and IFN-γ levels were available. From the public GEO dataset, GSE66099, GSE9960, GSE95233, GSE57065 were downloaded. Genes corresponding to 15 molecules were extracted from an expression array. A correlation matrix was formed for the 15 molecules and statistically significant molecular pairs were used as pairs for network analysis of coexpression. The number of molecular or gene expression pairs significantly correlated among the SIRS or control and sepsis groups are as follows for datasets: EMR, 15 and 15; GEO66099-1, 13 and 15; GEO9960, 13 and 11; GSE95233, 13 and 8; GSE66099-2, 15 and 14; GSE57065, 14 and 13, respectively. Network analysis revealed that network diameter, number of nodes and shortest path were equal to or lower in the sepsis group. The coexpression network in sepsis patients was relatively small sized and had lower shortest paths compared with the SIRS group or healthy control group. Cytokines with one degree (k = 1) are increased in sepsis group compared with SIRS or healthy control group. IL-9 and IL-2 were not included in network of sepsis group indicating that these cytokines showed no correlation with other cytokines. These data might imply that cytokines tend to be dysregulated in the sepsis group compared to that of SIRS or normal control groups.
52 schema:genre research_article
53 schema:inLanguage en
54 schema:isAccessibleForFree false
55 schema:isPartOf Nd0ebf32bbf224870863a979260d9f188
56 Nd7ee5b7361914a4bb2cc6388354292ed
57 sg:journal.1100922
58 schema:name Cytokine and molecular networks in sepsis cases: a network biology approach
59 schema:pagination 103-111
60 schema:productId N28a7d94b1962482f95b4850c2f7db8ae
61 N4bf3ddf7ab6f4eaebd2e7a17154936ba
62 N4f693ba4f8b64fc29d95dd8d66e2fcd1
63 N9176b04c43b64457967bda99b8018b86
64 Na83e0a53cf08406f8b6340e7321e3eac
65 schema:sameAs https://app.dimensions.ai/details/publication/pub.1111024058
66 https://doi.org/10.1684/ecn.2018.0414
67 schema:sdDatePublished 2019-04-11T13:18
68 schema:sdLicense https://scigraph.springernature.com/explorer/license/
69 schema:sdPublisher N232950f099b949408d45a5ca907d78e4
70 schema:url https://link.springer.com/10.1684%2Fecn.2018.0414
71 sgo:license sg:explorer/license/
72 sgo:sdDataset articles
73 rdf:type schema:ScholarlyArticle
74 N0105157d105a4edd9fd7c93395f19b44 rdf:first sg:person.07564035574.49
75 rdf:rest N4db9568c7ed8428e850ea9bb38511add
76 N1a5eb2fd6c73481b9fea3e05cbe80ee8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
77 schema:name Retrospective Studies
78 rdf:type schema:DefinedTerm
79 N232950f099b949408d45a5ca907d78e4 schema:name Springer Nature - SN SciGraph project
80 rdf:type schema:Organization
81 N28a7d94b1962482f95b4850c2f7db8ae schema:name dimensions_id
82 schema:value pub.1111024058
83 rdf:type schema:PropertyValue
84 N4bf3ddf7ab6f4eaebd2e7a17154936ba schema:name doi
85 schema:value 10.1684/ecn.2018.0414
86 rdf:type schema:PropertyValue
87 N4db9568c7ed8428e850ea9bb38511add rdf:first sg:person.01352610144.46
88 rdf:rest rdf:nil
89 N4f693ba4f8b64fc29d95dd8d66e2fcd1 schema:name nlm_unique_id
90 schema:value 9100879
91 rdf:type schema:PropertyValue
92 N5dd3277c653347369a39a331636aa8dc schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
93 schema:name Child, Preschool
94 rdf:type schema:DefinedTerm
95 N6845c347fc2e47f79948b8c0b912b002 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
96 schema:name Sepsis
97 rdf:type schema:DefinedTerm
98 N70e926bd1599458c90ef35645cc33901 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
99 schema:name Child
100 rdf:type schema:DefinedTerm
101 N76a9512850ce41669b05bc18fac3f469 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
102 schema:name Female
103 rdf:type schema:DefinedTerm
104 N8e6d6bc99e664d7e8d7cd0bf042f673d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
105 schema:name Databases, Factual
106 rdf:type schema:DefinedTerm
107 N9176b04c43b64457967bda99b8018b86 schema:name pubmed_id
108 schema:value 30547887
109 rdf:type schema:PropertyValue
110 N9d05223575a24952985d22f542a69941 rdf:first sg:person.01163541077.61
111 rdf:rest N0105157d105a4edd9fd7c93395f19b44
112 Na2b93186d49e406f8f86119bb3ca52dd schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
113 schema:name Humans
114 rdf:type schema:DefinedTerm
115 Na83e0a53cf08406f8b6340e7321e3eac schema:name readcube_id
116 schema:value d10f4fd679978e1a34cfe08042dc7bbe75a546aef481b387fcefb0a4f6e4e461
117 rdf:type schema:PropertyValue
118 Nba66fde527a541bf8ad7c8f71125f4f9 rdf:first sg:person.0630010543.71
119 rdf:rest Nf038d48618a7460cb82b51a61df87f3d
120 Nd0ebf32bbf224870863a979260d9f188 schema:volumeNumber 29
121 rdf:type schema:PublicationVolume
122 Nd7e690c8fd4c4443bba9d979081badfe schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
123 schema:name Adult
124 rdf:type schema:DefinedTerm
125 Nd7ee5b7361914a4bb2cc6388354292ed schema:issueNumber 3
126 rdf:type schema:PublicationIssue
127 Nf038d48618a7460cb82b51a61df87f3d rdf:first sg:person.0714317030.03
128 rdf:rest N9d05223575a24952985d22f542a69941
129 Nf48af6495e234a949c711507d48b1e70 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
130 schema:name Infant
131 rdf:type schema:DefinedTerm
132 Nf7e404d5f18d4426b3026977d97d1006 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
133 schema:name Male
134 rdf:type schema:DefinedTerm
135 Nfb636e02a65f4c9fa318f57a9339df0d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
136 schema:name Cytokines
137 rdf:type schema:DefinedTerm
138 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
139 schema:name Medical and Health Sciences
140 rdf:type schema:DefinedTerm
141 anzsrc-for:1107 schema:inDefinedTermSet anzsrc-for:
142 schema:name Immunology
143 rdf:type schema:DefinedTerm
144 sg:journal.1100922 schema:issn 1148-5493
145 1952-4005
146 schema:name European Cytokine Network
147 rdf:type schema:Periodical
148 sg:person.01163541077.61 schema:affiliation https://www.grid.ac/institutes/grid.411947.e
149 schema:familyName Lee
150 schema:givenName Seungok
151 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01163541077.61
152 rdf:type schema:Person
153 sg:person.01352610144.46 schema:affiliation https://www.grid.ac/institutes/grid.411947.e
154 schema:familyName Kim
155 schema:givenName Yonggoo
156 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01352610144.46
157 rdf:type schema:Person
158 sg:person.0630010543.71 schema:affiliation https://www.grid.ac/institutes/grid.411947.e
159 schema:familyName Jekarl
160 schema:givenName Dong Wook
161 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0630010543.71
162 rdf:type schema:Person
163 sg:person.0714317030.03 schema:affiliation https://www.grid.ac/institutes/grid.411947.e
164 schema:familyName Kim
165 schema:givenName Kyung Soo
166 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0714317030.03
167 rdf:type schema:Person
168 sg:person.07564035574.49 schema:affiliation https://www.grid.ac/institutes/grid.411947.e
169 schema:familyName Kim
170 schema:givenName Myungshin
171 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07564035574.49
172 rdf:type schema:Person
173 sg:pub.10.1038/nature01326 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033794061
174 https://doi.org/10.1038/nature01326
175 rdf:type schema:CreativeWork
176 sg:pub.10.1038/nmeth.2212 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026331197
177 https://doi.org/10.1038/nmeth.2212
178 rdf:type schema:CreativeWork
179 sg:pub.10.1038/nprot.2012.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015407882
180 https://doi.org/10.1038/nprot.2012.004
181 rdf:type schema:CreativeWork
182 sg:pub.10.1038/nrg1272 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018231980
183 https://doi.org/10.1038/nrg1272
184 rdf:type schema:CreativeWork
185 sg:pub.10.1038/nrg2918 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021371713
186 https://doi.org/10.1038/nrg2918
187 rdf:type schema:CreativeWork
188 sg:pub.10.1186/1471-2105-10-109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036359613
189 https://doi.org/10.1186/1471-2105-10-109
190 rdf:type schema:CreativeWork
191 sg:pub.10.1186/1471-2164-15-997 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037805312
192 https://doi.org/10.1186/1471-2164-15-997
193 rdf:type schema:CreativeWork
194 sg:pub.10.1186/1756-0381-4-10 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002056061
195 https://doi.org/10.1186/1756-0381-4-10
196 rdf:type schema:CreativeWork
197 sg:pub.10.1186/cc10274 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022380816
198 https://doi.org/10.1186/cc10274
199 rdf:type schema:CreativeWork
200 sg:pub.10.1186/cc5783 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004605172
201 https://doi.org/10.1186/cc5783
202 rdf:type schema:CreativeWork
203 sg:pub.10.1186/cc9392 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030309905
204 https://doi.org/10.1186/cc9392
205 rdf:type schema:CreativeWork
206 sg:pub.10.1186/s40635-014-0020-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007337554
207 https://doi.org/10.1186/s40635-014-0020-3
208 rdf:type schema:CreativeWork
209 https://doi.org/10.1001/jama.2011.1829 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006669572
210 rdf:type schema:CreativeWork
211 https://doi.org/10.1001/jama.2016.0287 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045696843
212 rdf:type schema:CreativeWork
213 https://doi.org/10.1001/jama.2016.0288 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016776662
214 rdf:type schema:CreativeWork
215 https://doi.org/10.1002/pmic.201000684 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051849365
216 rdf:type schema:CreativeWork
217 https://doi.org/10.1016/j.diagmicrobio.2012.12.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004417402
218 rdf:type schema:CreativeWork
219 https://doi.org/10.1016/j.humimm.2017.03.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084078899
220 rdf:type schema:CreativeWork
221 https://doi.org/10.1016/j.jinf.2016.01.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023580079
222 rdf:type schema:CreativeWork
223 https://doi.org/10.1056/nejmoa1415236 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039137824
224 rdf:type schema:CreativeWork
225 https://doi.org/10.1056/nejmra021333 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019375943
226 rdf:type schema:CreativeWork
227 https://doi.org/10.1056/nejmra1208623 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032706237
228 rdf:type schema:CreativeWork
229 https://doi.org/10.1089/jir.2014.0119 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059281553
230 rdf:type schema:CreativeWork
231 https://doi.org/10.1093/bioinformatics/btm254 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010833586
232 rdf:type schema:CreativeWork
233 https://doi.org/10.1097/ccm.0b013e31819b52fd schema:sameAs https://app.dimensions.ai/details/publication/pub.1045641395
234 rdf:type schema:CreativeWork
235 https://doi.org/10.1097/ccm.0b013e318258fb70 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049099601
236 rdf:type schema:CreativeWork
237 https://doi.org/10.1101/gad.1528707 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050597665
238 rdf:type schema:CreativeWork
239 https://doi.org/10.1126/scitranslmed.aaa5993 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035837481
240 rdf:type schema:CreativeWork
241 https://doi.org/10.1177/09680519010070020201 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043958244
242 rdf:type schema:CreativeWork
243 https://doi.org/10.1371/journal.pone.0005686 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012755725
244 rdf:type schema:CreativeWork
245 https://doi.org/10.1371/journal.pone.0028870 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020393737
246 rdf:type schema:CreativeWork
247 https://doi.org/10.1378/chest.101.6.1644 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006971593
248 rdf:type schema:CreativeWork
249 https://doi.org/10.1515/cclm-2014-0607 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007773945
250 rdf:type schema:CreativeWork
251 https://doi.org/10.1684/ecn.2011.0281 schema:sameAs https://app.dimensions.ai/details/publication/pub.1078404380
252 rdf:type schema:CreativeWork
253 https://www.grid.ac/institutes/grid.411947.e schema:alternateName Catholic University of Korea
254 schema:name Department of Laboratory Medicine, Incheon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
255 Department of Laboratory Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, 06591, Seoul, Republic of Korea
256 Department of Thoracic and Cardiovascular Surgery, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
257 Laboratory for Development and Evaluation Center, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
258 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...