Ontology type: schema:ScholarlyArticle Open Access: True
2019-12
AUTHORSJaehwan Ahn, Jun-Ho Ahn, Seokjoo Yoon, Yoon Sung Nam, Mi-Young Son, Jung-Hwa Oh
ABSTRACTBackground: Various hepatic models mimicking liver lobules have been investigated to evaluate the potential hepatotoxic effects of chemicals and drugs, but in vitro hepatic models of zonal hepatotoxicity have not yet been established. Herein, we developed a three-dimensional (3D) hepatic zonal channel to evaluate zone-specific hepatotoxicity. Based on the perivenous zone-3-like cytochrome P450 (CYP) expression patterns in metabolically active HepaRG cells treated with CHIR99021 (CHIR), which is an inducer of Wnt/β-catenin signaling, this culture model represents a novel tool for exploring hepatic zonation. Results: We generated and validated a 3D hepatic zonal channel model in which 3D HepaRG cells were well distributed in agarose hydrogel channels, and a linear gradient of CHIR was generated according to the zonal distance. According to the results from imaging analyses and bioanalytical experiments, acetaminophen (APAP) caused cytotoxicity in the zone-3 region of the 3D hepatic zonal channel, and the levels of nonphosphorylated β-catenin, CYP2E, and apoptotic proteins were remarkably increased in the zone-3-like region. Finally, the applicability of the 3D hepatic zonal channel model for the high-throughput screening of zonal hepatotoxicity was successfully evaluated using hepatotoxic drugs, including tamoxifen, bromobenzene, and APAP. Conclusions: The results indicated that tamoxifen induced cytotoxic effects, regardless of the zonal distance, while the zone-3-specific hepatotoxic drugs bromobenzene and APAP induced greater cytotoxic effects on cells in the zone-3-like region. This finding highlights the potential of our 3D hepatic zonation model as a valuable tool for replicating and evaluating zonal hepatotoxicity by mimicking the spatial features of liver lobules. More... »
PAGES22
http://scigraph.springernature.com/pub.10.1186/s13036-019-0148-5
DOIhttp://dx.doi.org/10.1186/s13036-019-0148-5
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1112593540
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/30886645
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/2008/1115",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Pharmacology and Pharmaceutical Sciences",
"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"
}
],
"author": [
{
"affiliation": {
"alternateName": "Korea Institute of Toxicology",
"id": "https://www.grid.ac/institutes/grid.418982.e",
"name": [
"Department of Material Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), 34141, Daejeon, Republic of Korea",
"Department of Predictive Toxicology, Korea Institute of Toxicology (KIT), 34114, Daejeon, Republic of Korea"
],
"type": "Organization"
},
"familyName": "Ahn",
"givenName": "Jaehwan",
"type": "Person"
},
{
"affiliation": {
"alternateName": "Korea Institute of Toxicology",
"id": "https://www.grid.ac/institutes/grid.418982.e",
"name": [
"Department of Predictive Toxicology, Korea Institute of Toxicology (KIT), 34114, Daejeon, Republic of Korea"
],
"type": "Organization"
},
"familyName": "Ahn",
"givenName": "Jun-Ho",
"type": "Person"
},
{
"affiliation": {
"alternateName": "Korea Institute of Toxicology",
"id": "https://www.grid.ac/institutes/grid.418982.e",
"name": [
"Department of Predictive Toxicology, Korea Institute of Toxicology (KIT), 34114, Daejeon, Republic of Korea"
],
"type": "Organization"
},
"familyName": "Yoon",
"givenName": "Seokjoo",
"type": "Person"
},
{
"affiliation": {
"alternateName": "Korea Advanced Institute of Science and Technology",
"id": "https://www.grid.ac/institutes/grid.37172.30",
"name": [
"Department of Material Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), 34141, Daejeon, Republic of Korea"
],
"type": "Organization"
},
"familyName": "Nam",
"givenName": "Yoon Sung",
"type": "Person"
},
{
"affiliation": {
"alternateName": "Korea University of Science and Technology",
"id": "https://www.grid.ac/institutes/grid.412786.e",
"name": [
"Stem Cell Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), 34141, Daejeon, Republic of Korea",
"Department of Functional Genomics, KRIBB School of Bioscience, Korea University of Science and Technology (UST), 34113, Daejeon, Republic of Korea"
],
"type": "Organization"
},
"familyName": "Son",
"givenName": "Mi-Young",
"type": "Person"
},
{
"affiliation": {
"alternateName": "Korea Institute of Toxicology",
"id": "https://www.grid.ac/institutes/grid.418982.e",
"name": [
"Department of Predictive Toxicology, Korea Institute of Toxicology (KIT), 34114, Daejeon, Republic of Korea"
],
"type": "Organization"
},
"familyName": "Oh",
"givenName": "Jung-Hwa",
"type": "Person"
}
],
"citation": [
{
"id": "https://doi.org/10.1124/dmd.109.030197",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1003343512"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/b978-0-12-385233-5.00005-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1003445294"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1124/mol.114.094797",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1006137255"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1021/bm4015039",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1006609017"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1042/bj3290017",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1007253335"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1042/bj3290017",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1007253335"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/toxsci/kfi052",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1008160726"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/hep.510310201",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1008519492"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/978-1-4419-7107-4_2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1008702764",
"https://doi.org/10.1007/978-1-4419-7107-4_2"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/srep26868",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1009614741",
"https://doi.org/10.1038/srep26868"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1146/annurev.nu.16.070196.001143",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1009673344"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.bios.2013.07.019",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1010494491"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ki.1997.53",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1011544280",
"https://doi.org/10.1038/ki.1997.53"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s10565-011-9208-4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1011794647",
"https://doi.org/10.1007/s10565-011-9208-4"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s10565-011-9208-4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1011794647",
"https://doi.org/10.1007/s10565-011-9208-4"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/biot.200700228",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1012544415"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.devcel.2006.03.015",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1012581109"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ncb3349",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1012767848",
"https://doi.org/10.1038/ncb3349"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.proghi.2006.12.001",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1013775702"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1023/a:1023234429596",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1018406671",
"https://doi.org/10.1023/a:1023234429596"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/bies.20485",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1018465052"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.cbi.2006.12.003",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1019687345"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s0005-8165(76)80083-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1021316627"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1124/mol.114.097402",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1021988890"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/ar.1091190103",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1027913350"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.biomaterials.2014.03.020",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1028105615"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1097/fjc.0000000000000429",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1035193951"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1097/fjc.0000000000000429",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1035193951"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1056/nejmra021844",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1035982169"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1006/rtph.2000.1399",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036505614"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1042/bj20121284",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036594313"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1042/bj20121284",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036594313"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/jbt.10085",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1039359315"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.redox.2017.01.012",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1042137012"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1039/c6tx00101g",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1042382011"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/toxsci/kft021",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1042568964"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1073/pnas.1524510113",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1043048110"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.14218/jcth.2014.00014",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1044823153"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.apsb.2016.07.014",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1045582343"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/0163-7258(92)90055-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1046910372"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/0163-7258(92)90055-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1046910372"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/bit.10569",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1047436462"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1073/pnas.1317731111",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1050414309"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.vascn.2010.04.013",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1051491760"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.2133/dmpk.dmpk-10-rv-089",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1051744378"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1080/03602530601093489",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1053424820"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1055/s-2008-1040554",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1057535947"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1080/01926230590522121",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1058308211"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1080/01926230590522121",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1058308211"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/toxsci/kfv177",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1060056834"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/nan.12396",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1083909380"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1096/fj.201700504r",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1091381792"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/emm.2017.226",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1099669803",
"https://doi.org/10.1038/emm.2017.226"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00204-018-2152-9",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1100559716",
"https://doi.org/10.1007/s00204-018-2152-9"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/s41467-018-05450-8",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1105886897",
"https://doi.org/10.1038/s41467-018-05450-8"
],
"type": "CreativeWork"
}
],
"datePublished": "2019-12",
"datePublishedReg": "2019-12-01",
"description": "Background: Various hepatic models mimicking liver lobules have been investigated to evaluate the potential hepatotoxic effects of chemicals and drugs, but in vitro hepatic models of zonal hepatotoxicity have not yet been established. Herein, we developed a three-dimensional (3D) hepatic zonal channel to evaluate zone-specific hepatotoxicity. Based on the perivenous zone-3-like cytochrome P450 (CYP) expression patterns in metabolically active HepaRG cells treated with CHIR99021 (CHIR), which is an inducer of Wnt/\u03b2-catenin signaling, this culture model represents a novel tool for exploring hepatic zonation.\nResults: We generated and validated a 3D hepatic zonal channel model in which 3D HepaRG cells were well distributed in agarose hydrogel channels, and a linear gradient of CHIR was generated according to the zonal distance. According to the results from imaging analyses and bioanalytical experiments, acetaminophen (APAP) caused cytotoxicity in the zone-3 region of the 3D hepatic zonal channel, and the levels of nonphosphorylated \u03b2-catenin, CYP2E, and apoptotic proteins were remarkably increased in the zone-3-like region. Finally, the applicability of the 3D hepatic zonal channel model for the high-throughput screening of zonal hepatotoxicity was successfully evaluated using hepatotoxic drugs, including tamoxifen, bromobenzene, and APAP.\nConclusions: The results indicated that tamoxifen induced cytotoxic effects, regardless of the zonal distance, while the zone-3-specific hepatotoxic drugs bromobenzene and APAP induced greater cytotoxic effects on cells in the zone-3-like region. This finding highlights the potential of our 3D hepatic zonation model as a valuable tool for replicating and evaluating zonal hepatotoxicity by mimicking the spatial features of liver lobules.",
"genre": "research_article",
"id": "sg:pub.10.1186/s13036-019-0148-5",
"inLanguage": [
"en"
],
"isAccessibleForFree": true,
"isFundedItemOf": [
{
"id": "sg:grant.7491703",
"type": "MonetaryGrant"
}
],
"isPartOf": [
{
"id": "sg:journal.1038668",
"issn": [
"1754-1611"
],
"name": "Journal of Biological Engineering",
"type": "Periodical"
},
{
"issueNumber": "1",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "13"
}
],
"name": "Human three-dimensional in vitro model of hepatic zonation to predict zonal hepatotoxicity",
"pagination": "22",
"productId": [
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"56aea597dfc41070dccf9276d8c18bc61e7dd4fcf4023dbe644ad8a8aec69b06"
]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"30886645"
]
},
{
"name": "nlm_unique_id",
"type": "PropertyValue",
"value": [
"101306640"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1186/s13036-019-0148-5"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1112593540"
]
}
],
"sameAs": [
"https://doi.org/10.1186/s13036-019-0148-5",
"https://app.dimensions.ai/details/publication/pub.1112593540"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-11T13:17",
"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_78935_00000001.jsonl",
"type": "ScholarlyArticle",
"url": "https://link.springer.com/10.1186%2Fs13036-019-0148-5"
}
]Download the RDF metadata as: json-ld nt turtle xml License info
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.10.1186/s13036-019-0148-5'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s13036-019-0148-5'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13036-019-0148-5'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13036-019-0148-5'
This table displays all metadata directly associated to this object as RDF triples.
263 TRIPLES
21 PREDICATES
78 URIs
21 LITERALS
9 BLANK NODES