Association between skeletal muscle mass and serum concentrations of lipoprotein lipase, GPIHBP1, and hepatic triglyceride lipase in young Japanese men. View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Ryutaro Matsumoto, Katsuhiko Tsunekawa, Yoshifumi Shoho, Yoshimaro Yanagawa, Nobuo Kotajima, Shingo Matsumoto, Osamu Araki, Takao Kimura, Katsuyuki Nakajima, Masami Murakami

ABSTRACT

BACKGROUND: Two important regulators for circulating lipid metabolisms are lipoprotein lipase (LPL) and hepatic triglyceride lipase (HTGL). In relation to this, glycosylphosphatidylinositol anchored high-density lipoprotein binding protein 1 (GPIHBP1) has been shown to have a vital role in LPL lipolytic processing. However, the relationships between skeletal muscle mass and lipid metabolism, including LPL, GPIHBP1, and HTGL, remain to be elucidated. Demonstration of these relationships may lead to clarification of the metabolic dysfunctions caused by sarcopenia. In this study, these relationships were investigated in young Japanese men who had no age-related factors; participants included wrestling athletes with abundant skeletal muscle. METHODS: A total of 111 young Japanese men who were not taking medications were enrolled; 70 wrestling athletes and 41 control students were included. The participants' body compositions, serum concentrations of lipoprotein, LPL, GPIHBP1 and HTGL and thyroid function test results were determined under conditions of no extreme dietary restrictions and exercises. RESULTS: Compared with the control participants, wrestling athletes had significantly higher skeletal muscle index (SMI) (p < 0.001), higher serum concentrations of LPL (p < 0.001) and GPIHBP1 (p < 0.001), and lower fat mass index (p = 0.024). Kruskal-Wallis tests with Bonferroni multiple comparison tests showed that serum LPL and GPIHBP1 concentrations were significantly higher in the participants with higher SMI. Spearman's correlation analyses showed that SMI was positively correlated with LPL (ρ = 0.341, p < 0.001) and GPIHBP1 (ρ = 0.309, p = 0.001) concentration. The serum concentrations of LPL and GPIHBP1 were also inversely correlated with serum concentrations of triglyceride (LPL, ρ = - 0.198, p = 0.037; GPIHBP1, ρ = - 0.249, p = 0.008). Serum HTGL concentration was positively correlated with serum concentrations of total cholesterol (ρ = 0.308, p = 0.001), low-density lipoprotein-cholesterol (ρ = 0.336, p < 0.001), and free 3,5,3'-triiodothyronine (ρ = 0.260, p = 0.006), but not with SMI. CONCLUSIONS: The results suggest that increased skeletal muscle mass leads to improvements in energy metabolism by promoting triglyceride-rich lipoprotein hydrolysis through the increase in circulating LPL and GPIHBP1. More... »

PAGES

84

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12944-019-1014-7

DOI

http://dx.doi.org/10.1186/s12944-019-1014-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1113184503

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30947712


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/2008/1103", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Clinical 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": "Gunma University", 
          "id": "https://www.grid.ac/institutes/grid.256642.1", 
          "name": [
            "Department of Clinical Laboratory Medicine, Gunma University Graduate School of Medicine, Maebashi, 371-8511, Japan."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Matsumoto", 
        "givenName": "Ryutaro", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Gunma University", 
          "id": "https://www.grid.ac/institutes/grid.256642.1", 
          "name": [
            "Department of Clinical Laboratory Medicine, Gunma University Graduate School of Medicine, Maebashi, 371-8511, Japan. ktsune@gunma-u.ac.jp."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tsunekawa", 
        "givenName": "Katsuhiko", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Gunma University", 
          "id": "https://www.grid.ac/institutes/grid.256642.1", 
          "name": [
            "Department of Clinical Laboratory Medicine, Gunma University Graduate School of Medicine, Maebashi, 371-8511, Japan.", 
            "Faculty of Education, Ikuei University, Takasaki, 370-0011, Japan."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shoho", 
        "givenName": "Yoshifumi", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Gunma University", 
          "id": "https://www.grid.ac/institutes/grid.256642.1", 
          "name": [
            "Department of Clinical Laboratory Medicine, Gunma University Graduate School of Medicine, Maebashi, 371-8511, Japan.", 
            "Faculty of Education, Ikuei University, Takasaki, 370-0011, Japan."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yanagawa", 
        "givenName": "Yoshimaro", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Gunma University", 
          "id": "https://www.grid.ac/institutes/grid.256642.1", 
          "name": [
            "Department of Clinical Laboratory Medicine, Gunma University Graduate School of Medicine, Maebashi, 371-8511, Japan.", 
            "School of Medical Technology, Faculty of Health Science, Gunma Paz University, Takasaki, 370-0006, Japan."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kotajima", 
        "givenName": "Nobuo", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Nippon Sport Science University", 
          "id": "https://www.grid.ac/institutes/grid.412200.5", 
          "name": [
            "Graduate School of Health and Sport Science, Nippon Sport Science University, Yokohama, 227-0033, Japan."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Matsumoto", 
        "givenName": "Shingo", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Gunma University", 
          "id": "https://www.grid.ac/institutes/grid.256642.1", 
          "name": [
            "Department of Clinical Laboratory Medicine, Gunma University Graduate School of Medicine, Maebashi, 371-8511, Japan."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Araki", 
        "givenName": "Osamu", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Gunma University", 
          "id": "https://www.grid.ac/institutes/grid.256642.1", 
          "name": [
            "Department of Clinical Laboratory Medicine, Gunma University Graduate School of Medicine, Maebashi, 371-8511, Japan."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kimura", 
        "givenName": "Takao", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Gunma University", 
          "id": "https://www.grid.ac/institutes/grid.256642.1", 
          "name": [
            "Department of Clinical Laboratory Medicine, Gunma University Graduate School of Medicine, Maebashi, 371-8511, Japan."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nakajima", 
        "givenName": "Katsuyuki", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Gunma University", 
          "id": "https://www.grid.ac/institutes/grid.256642.1", 
          "name": [
            "Department of Clinical Laboratory Medicine, Gunma University Graduate School of Medicine, Maebashi, 371-8511, Japan."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Murakami", 
        "givenName": "Masami", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.cca.2014.10.029", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002467176"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jcb.25077", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008603819"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1507/endocrj.k09e-359", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009740053"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1507/endocrj.k09e-359", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009740053"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cca.2014.07.020", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009861963"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5551/jat.9.163", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010018448"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10545-011-9406-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015220063", 
          "https://doi.org/10.1007/s10545-011-9406-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ejcn.2012.43", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016724845", 
          "https://doi.org/10.1038/ejcn.2012.43"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0070-2153(05)68005-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020793525"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0070-2153(05)68005-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020793525"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1194/jlr.m002717", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024123066"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0112718", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026406969"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/hc5001.100795", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027663342"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circresaha.116.305085", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028405305"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circresaha.116.305085", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028405305"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circgenetics.109.908905", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028594616"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circgenetics.109.908905", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028594616"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0021-9150(99)00012-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028736826"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.diabres.2006.08.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028765935"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0009-8981(93)90144-s", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029491201"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0009-8981(93)90144-s", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029491201"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.atv.10.4.497", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030639423"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1096/fj.03-0428com", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030749751"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2739/kurumemedj.53.29", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031581694"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/10408369891234273", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032196044"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0021-9150(00)00413-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036224251"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1046/j.1365-2265.2003.01762.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036783100"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.bbalip.2011.09.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037785891"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-2796.2011.02361.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039182305"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0009-8981(99)00105-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040074848"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tem.2016.04.013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040093237"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.diabres.2005.09.016", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041789381"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5551/jat.2337", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042487170"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.bbalip.2014.03.013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045004199"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1113/jphysiol.2002.016832", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045081344"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1146/annurev.bi.49.070180.003315", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047159530"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s40618-013-0011-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047238381", 
          "https://doi.org/10.1007/s40618-013-0011-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3810/psm.2009.04.1678", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052057441"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cca.2015.01.016", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053090723"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1055/s-2001-16230", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057409161"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1055/s-2005-873020", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057449842"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1089/10507250252949405", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059204304"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1089/thy.2015.0140", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059322038"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.atv.15.8.1086", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1063334079"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1210/jc.2011-1444", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064292920"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1210/jc.85.3.977", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064301325"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jappl.2000.89.1.176", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1074670958"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1075105446", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1080284174", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1082771815", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmoa1611930", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084540243"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmoa1611930", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084540243"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1194/jlr.m075432", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1086110994"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cca.2017.10.017", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092293079"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jacl.2017.10.022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092482790"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jacl.2017.10.022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092482790"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jacl.2017.10.022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092482790"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cca.2017.11.021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092939972"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cca.2017.11.021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092939972"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/ageing/afy169", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1107246097"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/ageing/afy169", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1107246097"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-12", 
    "datePublishedReg": "2019-12-01", 
    "description": "BACKGROUND: Two important regulators for circulating lipid metabolisms are lipoprotein lipase (LPL) and hepatic triglyceride lipase (HTGL). In relation to this, glycosylphosphatidylinositol anchored high-density lipoprotein binding protein 1 (GPIHBP1) has been shown to have a vital role in LPL lipolytic processing. However, the relationships between skeletal muscle mass and lipid metabolism, including LPL, GPIHBP1, and HTGL, remain to be elucidated. Demonstration of these relationships may lead to clarification of the metabolic dysfunctions caused by sarcopenia. In this study, these relationships were investigated in young Japanese men who had no age-related factors; participants included wrestling athletes with abundant skeletal muscle.\nMETHODS: A total of 111 young Japanese men who were not taking medications were enrolled; 70 wrestling athletes and 41 control students were included. The participants' body compositions, serum concentrations of lipoprotein, LPL, GPIHBP1 and HTGL and thyroid function test results were determined under conditions of no extreme dietary restrictions and exercises.\nRESULTS: Compared with the control participants, wrestling athletes had significantly higher skeletal muscle index (SMI) (p\u2009<\u20090.001), higher serum concentrations of LPL (p\u2009<\u20090.001) and GPIHBP1 (p\u2009<\u20090.001), and lower fat mass index (p\u2009=\u20090.024). Kruskal-Wallis tests with Bonferroni multiple comparison tests showed that serum LPL and GPIHBP1 concentrations were significantly higher in the participants with higher SMI. Spearman's correlation analyses showed that SMI was positively correlated with LPL (\u03c1\u2009=\u20090.341, p\u2009<\u20090.001) and GPIHBP1 (\u03c1\u2009=\u20090.309, p\u2009=\u20090.001) concentration. The serum concentrations of LPL and GPIHBP1 were also inversely correlated with serum concentrations of triglyceride (LPL, \u03c1\u2009=\u2009-\u20090.198, p\u2009=\u20090.037; GPIHBP1, \u03c1\u2009=\u2009-\u20090.249, p\u2009=\u20090.008). Serum HTGL concentration was positively correlated with serum concentrations of total cholesterol (\u03c1\u2009=\u20090.308, p\u2009=\u20090.001), low-density lipoprotein-cholesterol (\u03c1\u2009=\u20090.336, p\u2009<\u20090.001), and free 3,5,3'-triiodothyronine (\u03c1\u2009=\u20090.260, p\u2009=\u20090.006), but not with SMI.\nCONCLUSIONS: The results suggest that increased skeletal muscle mass leads to improvements in energy metabolism by promoting triglyceride-rich lipoprotein hydrolysis through the increase in circulating LPL and GPIHBP1.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/s12944-019-1014-7", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1031029", 
        "issn": [
          "1476-511X"
        ], 
        "name": "Lipids in Health and Disease", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "18"
      }
    ], 
    "name": "Association between skeletal muscle mass and serum concentrations of lipoprotein lipase, GPIHBP1, and hepatic triglyceride lipase in young Japanese men.", 
    "pagination": "84", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s12944-019-1014-7"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1113184503"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101147696"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30947712"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s12944-019-1014-7", 
      "https://app.dimensions.ai/details/publication/pub.1113184503"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-15T09:04", 
    "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/v90/0000000375_0000000375/records_91469_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://lipidworld.biomedcentral.com/articles/10.1186/s12944-019-1014-7"
  }
]
 

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.10.1186/s12944-019-1014-7'

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/s12944-019-1014-7'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12944-019-1014-7'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12944-019-1014-7'


 

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

276 TRIPLES      21 PREDICATES      79 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s12944-019-1014-7 schema:about anzsrc-for:11
2 anzsrc-for:1103
3 schema:author Nddd7b839517a413fab95bd7da5836e89
4 schema:citation sg:pub.10.1007/s10545-011-9406-5
5 sg:pub.10.1007/s40618-013-0011-3
6 sg:pub.10.1038/ejcn.2012.43
7 https://app.dimensions.ai/details/publication/pub.1075105446
8 https://app.dimensions.ai/details/publication/pub.1080284174
9 https://app.dimensions.ai/details/publication/pub.1082771815
10 https://doi.org/10.1002/jcb.25077
11 https://doi.org/10.1016/0009-8981(93)90144-s
12 https://doi.org/10.1016/j.bbalip.2011.09.008
13 https://doi.org/10.1016/j.bbalip.2014.03.013
14 https://doi.org/10.1016/j.cca.2014.07.020
15 https://doi.org/10.1016/j.cca.2014.10.029
16 https://doi.org/10.1016/j.cca.2015.01.016
17 https://doi.org/10.1016/j.cca.2017.10.017
18 https://doi.org/10.1016/j.cca.2017.11.021
19 https://doi.org/10.1016/j.diabres.2005.09.016
20 https://doi.org/10.1016/j.diabres.2006.08.004
21 https://doi.org/10.1016/j.jacl.2017.10.022
22 https://doi.org/10.1016/j.tem.2016.04.013
23 https://doi.org/10.1016/s0009-8981(99)00105-9
24 https://doi.org/10.1016/s0021-9150(00)00413-5
25 https://doi.org/10.1016/s0021-9150(99)00012-x
26 https://doi.org/10.1016/s0070-2153(05)68005-2
27 https://doi.org/10.1046/j.1365-2265.2003.01762.x
28 https://doi.org/10.1055/s-2001-16230
29 https://doi.org/10.1055/s-2005-873020
30 https://doi.org/10.1056/nejmoa1611930
31 https://doi.org/10.1080/10408369891234273
32 https://doi.org/10.1089/10507250252949405
33 https://doi.org/10.1089/thy.2015.0140
34 https://doi.org/10.1093/ageing/afy169
35 https://doi.org/10.1096/fj.03-0428com
36 https://doi.org/10.1111/j.1365-2796.2011.02361.x
37 https://doi.org/10.1113/jphysiol.2002.016832
38 https://doi.org/10.1146/annurev.bi.49.070180.003315
39 https://doi.org/10.1152/jappl.2000.89.1.176
40 https://doi.org/10.1161/01.atv.10.4.497
41 https://doi.org/10.1161/01.atv.15.8.1086
42 https://doi.org/10.1161/circgenetics.109.908905
43 https://doi.org/10.1161/circresaha.116.305085
44 https://doi.org/10.1161/hc5001.100795
45 https://doi.org/10.1194/jlr.m002717
46 https://doi.org/10.1194/jlr.m075432
47 https://doi.org/10.1210/jc.2011-1444
48 https://doi.org/10.1210/jc.85.3.977
49 https://doi.org/10.1371/journal.pone.0112718
50 https://doi.org/10.1507/endocrj.k09e-359
51 https://doi.org/10.2739/kurumemedj.53.29
52 https://doi.org/10.3810/psm.2009.04.1678
53 https://doi.org/10.5551/jat.2337
54 https://doi.org/10.5551/jat.9.163
55 schema:datePublished 2019-12
56 schema:datePublishedReg 2019-12-01
57 schema:description BACKGROUND: Two important regulators for circulating lipid metabolisms are lipoprotein lipase (LPL) and hepatic triglyceride lipase (HTGL). In relation to this, glycosylphosphatidylinositol anchored high-density lipoprotein binding protein 1 (GPIHBP1) has been shown to have a vital role in LPL lipolytic processing. However, the relationships between skeletal muscle mass and lipid metabolism, including LPL, GPIHBP1, and HTGL, remain to be elucidated. Demonstration of these relationships may lead to clarification of the metabolic dysfunctions caused by sarcopenia. In this study, these relationships were investigated in young Japanese men who had no age-related factors; participants included wrestling athletes with abundant skeletal muscle. METHODS: A total of 111 young Japanese men who were not taking medications were enrolled; 70 wrestling athletes and 41 control students were included. The participants' body compositions, serum concentrations of lipoprotein, LPL, GPIHBP1 and HTGL and thyroid function test results were determined under conditions of no extreme dietary restrictions and exercises. RESULTS: Compared with the control participants, wrestling athletes had significantly higher skeletal muscle index (SMI) (p < 0.001), higher serum concentrations of LPL (p < 0.001) and GPIHBP1 (p < 0.001), and lower fat mass index (p = 0.024). Kruskal-Wallis tests with Bonferroni multiple comparison tests showed that serum LPL and GPIHBP1 concentrations were significantly higher in the participants with higher SMI. Spearman's correlation analyses showed that SMI was positively correlated with LPL (ρ = 0.341, p < 0.001) and GPIHBP1 (ρ = 0.309, p = 0.001) concentration. The serum concentrations of LPL and GPIHBP1 were also inversely correlated with serum concentrations of triglyceride (LPL, ρ = - 0.198, p = 0.037; GPIHBP1, ρ = - 0.249, p = 0.008). Serum HTGL concentration was positively correlated with serum concentrations of total cholesterol (ρ = 0.308, p = 0.001), low-density lipoprotein-cholesterol (ρ = 0.336, p < 0.001), and free 3,5,3'-triiodothyronine (ρ = 0.260, p = 0.006), but not with SMI. CONCLUSIONS: The results suggest that increased skeletal muscle mass leads to improvements in energy metabolism by promoting triglyceride-rich lipoprotein hydrolysis through the increase in circulating LPL and GPIHBP1.
58 schema:genre research_article
59 schema:inLanguage en
60 schema:isAccessibleForFree true
61 schema:isPartOf N90e58408fdba4676911bafe72214d18e
62 Ndf369f0eab8242a8a4465ebce6a9ab2a
63 sg:journal.1031029
64 schema:name Association between skeletal muscle mass and serum concentrations of lipoprotein lipase, GPIHBP1, and hepatic triglyceride lipase in young Japanese men.
65 schema:pagination 84
66 schema:productId N19fc9daf6bf54d3c8df34818f1b87276
67 N3c3dbe8484b34029b1ad23e9da8a34dd
68 N6651b23801ff40609329398a6e4d0bca
69 Nefab4d1432ea4deeb6c6c24eec9cc38d
70 schema:sameAs https://app.dimensions.ai/details/publication/pub.1113184503
71 https://doi.org/10.1186/s12944-019-1014-7
72 schema:sdDatePublished 2019-04-15T09:04
73 schema:sdLicense https://scigraph.springernature.com/explorer/license/
74 schema:sdPublisher N8f3bdf75128d4098aa6253a25ee463c7
75 schema:url https://lipidworld.biomedcentral.com/articles/10.1186/s12944-019-1014-7
76 sgo:license sg:explorer/license/
77 sgo:sdDataset articles
78 rdf:type schema:ScholarlyArticle
79 N19fc9daf6bf54d3c8df34818f1b87276 schema:name pubmed_id
80 schema:value 30947712
81 rdf:type schema:PropertyValue
82 N349df99d25ac4745bb4ff10f37de22e8 rdf:first Nd3f2d46b879c418abcc6c448408b9ba9
83 rdf:rest Naf67ba69f2dc454d8bf6109c65aa72a1
84 N38c0d0907c2f4c31a591e46a5c59668b schema:affiliation https://www.grid.ac/institutes/grid.256642.1
85 schema:familyName Araki
86 schema:givenName Osamu
87 rdf:type schema:Person
88 N3c3dbe8484b34029b1ad23e9da8a34dd schema:name dimensions_id
89 schema:value pub.1113184503
90 rdf:type schema:PropertyValue
91 N43bcac4096d54bc7bc8610c534425ef9 rdf:first Na60176aa22744a5fa3662f53d14a79f9
92 rdf:rest Nc79a4ddb9c304fa8b90f3e9a29c8b032
93 N4affb5d8d5b24c209db946dab14d2eae rdf:first Nad94f3149deb4290af8cbdbeead1fd75
94 rdf:rest Nfd452b6c277c440e876f746e39c64b38
95 N555f8b31a3314bc6aaa4abee3853001e schema:affiliation https://www.grid.ac/institutes/grid.256642.1
96 schema:familyName Kimura
97 schema:givenName Takao
98 rdf:type schema:Person
99 N5e959bc85a50482c8aeb15b5aa602b56 rdf:first Nde7c2cb007f447aabf7aa1a0e66608a2
100 rdf:rest rdf:nil
101 N6651b23801ff40609329398a6e4d0bca schema:name doi
102 schema:value 10.1186/s12944-019-1014-7
103 rdf:type schema:PropertyValue
104 N693f6865ce754af2bcb8b3f4d4e65e2c schema:affiliation https://www.grid.ac/institutes/grid.256642.1
105 schema:familyName Kotajima
106 schema:givenName Nobuo
107 rdf:type schema:Person
108 N7c32cb87611a40539dd434ce6ad2a505 schema:affiliation https://www.grid.ac/institutes/grid.256642.1
109 schema:familyName Matsumoto
110 schema:givenName Ryutaro
111 rdf:type schema:Person
112 N8f3bdf75128d4098aa6253a25ee463c7 schema:name Springer Nature - SN SciGraph project
113 rdf:type schema:Organization
114 N90e58408fdba4676911bafe72214d18e schema:volumeNumber 18
115 rdf:type schema:PublicationVolume
116 N93698997d633403fa76880fd10042c2a rdf:first N555f8b31a3314bc6aaa4abee3853001e
117 rdf:rest Na0b4eb3fa5794b12a25d3316584db23d
118 Na0b4eb3fa5794b12a25d3316584db23d rdf:first Nebbaffb82cb1480caac9ac19a56d1ada
119 rdf:rest N5e959bc85a50482c8aeb15b5aa602b56
120 Na60176aa22744a5fa3662f53d14a79f9 schema:affiliation https://www.grid.ac/institutes/grid.412200.5
121 schema:familyName Matsumoto
122 schema:givenName Shingo
123 rdf:type schema:Person
124 Nad75db7f9c794648a0d4ef51d2a8f5c3 schema:affiliation https://www.grid.ac/institutes/grid.256642.1
125 schema:familyName Shoho
126 schema:givenName Yoshifumi
127 rdf:type schema:Person
128 Nad94f3149deb4290af8cbdbeead1fd75 schema:affiliation https://www.grid.ac/institutes/grid.256642.1
129 schema:familyName Yanagawa
130 schema:givenName Yoshimaro
131 rdf:type schema:Person
132 Naf67ba69f2dc454d8bf6109c65aa72a1 rdf:first Nad75db7f9c794648a0d4ef51d2a8f5c3
133 rdf:rest N4affb5d8d5b24c209db946dab14d2eae
134 Nc79a4ddb9c304fa8b90f3e9a29c8b032 rdf:first N38c0d0907c2f4c31a591e46a5c59668b
135 rdf:rest N93698997d633403fa76880fd10042c2a
136 Nd3f2d46b879c418abcc6c448408b9ba9 schema:affiliation https://www.grid.ac/institutes/grid.256642.1
137 schema:familyName Tsunekawa
138 schema:givenName Katsuhiko
139 rdf:type schema:Person
140 Nddd7b839517a413fab95bd7da5836e89 rdf:first N7c32cb87611a40539dd434ce6ad2a505
141 rdf:rest N349df99d25ac4745bb4ff10f37de22e8
142 Nde7c2cb007f447aabf7aa1a0e66608a2 schema:affiliation https://www.grid.ac/institutes/grid.256642.1
143 schema:familyName Murakami
144 schema:givenName Masami
145 rdf:type schema:Person
146 Ndf369f0eab8242a8a4465ebce6a9ab2a schema:issueNumber 1
147 rdf:type schema:PublicationIssue
148 Nebbaffb82cb1480caac9ac19a56d1ada schema:affiliation https://www.grid.ac/institutes/grid.256642.1
149 schema:familyName Nakajima
150 schema:givenName Katsuyuki
151 rdf:type schema:Person
152 Nefab4d1432ea4deeb6c6c24eec9cc38d schema:name nlm_unique_id
153 schema:value 101147696
154 rdf:type schema:PropertyValue
155 Nfd452b6c277c440e876f746e39c64b38 rdf:first N693f6865ce754af2bcb8b3f4d4e65e2c
156 rdf:rest N43bcac4096d54bc7bc8610c534425ef9
157 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
158 schema:name Medical and Health Sciences
159 rdf:type schema:DefinedTerm
160 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
161 schema:name Clinical Sciences
162 rdf:type schema:DefinedTerm
163 sg:journal.1031029 schema:issn 1476-511X
164 schema:name Lipids in Health and Disease
165 rdf:type schema:Periodical
166 sg:pub.10.1007/s10545-011-9406-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015220063
167 https://doi.org/10.1007/s10545-011-9406-5
168 rdf:type schema:CreativeWork
169 sg:pub.10.1007/s40618-013-0011-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047238381
170 https://doi.org/10.1007/s40618-013-0011-3
171 rdf:type schema:CreativeWork
172 sg:pub.10.1038/ejcn.2012.43 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016724845
173 https://doi.org/10.1038/ejcn.2012.43
174 rdf:type schema:CreativeWork
175 https://app.dimensions.ai/details/publication/pub.1075105446 schema:CreativeWork
176 https://app.dimensions.ai/details/publication/pub.1080284174 schema:CreativeWork
177 https://app.dimensions.ai/details/publication/pub.1082771815 schema:CreativeWork
178 https://doi.org/10.1002/jcb.25077 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008603819
179 rdf:type schema:CreativeWork
180 https://doi.org/10.1016/0009-8981(93)90144-s schema:sameAs https://app.dimensions.ai/details/publication/pub.1029491201
181 rdf:type schema:CreativeWork
182 https://doi.org/10.1016/j.bbalip.2011.09.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037785891
183 rdf:type schema:CreativeWork
184 https://doi.org/10.1016/j.bbalip.2014.03.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045004199
185 rdf:type schema:CreativeWork
186 https://doi.org/10.1016/j.cca.2014.07.020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009861963
187 rdf:type schema:CreativeWork
188 https://doi.org/10.1016/j.cca.2014.10.029 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002467176
189 rdf:type schema:CreativeWork
190 https://doi.org/10.1016/j.cca.2015.01.016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053090723
191 rdf:type schema:CreativeWork
192 https://doi.org/10.1016/j.cca.2017.10.017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092293079
193 rdf:type schema:CreativeWork
194 https://doi.org/10.1016/j.cca.2017.11.021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092939972
195 rdf:type schema:CreativeWork
196 https://doi.org/10.1016/j.diabres.2005.09.016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041789381
197 rdf:type schema:CreativeWork
198 https://doi.org/10.1016/j.diabres.2006.08.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028765935
199 rdf:type schema:CreativeWork
200 https://doi.org/10.1016/j.jacl.2017.10.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092482790
201 rdf:type schema:CreativeWork
202 https://doi.org/10.1016/j.tem.2016.04.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040093237
203 rdf:type schema:CreativeWork
204 https://doi.org/10.1016/s0009-8981(99)00105-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040074848
205 rdf:type schema:CreativeWork
206 https://doi.org/10.1016/s0021-9150(00)00413-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036224251
207 rdf:type schema:CreativeWork
208 https://doi.org/10.1016/s0021-9150(99)00012-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1028736826
209 rdf:type schema:CreativeWork
210 https://doi.org/10.1016/s0070-2153(05)68005-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020793525
211 rdf:type schema:CreativeWork
212 https://doi.org/10.1046/j.1365-2265.2003.01762.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1036783100
213 rdf:type schema:CreativeWork
214 https://doi.org/10.1055/s-2001-16230 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057409161
215 rdf:type schema:CreativeWork
216 https://doi.org/10.1055/s-2005-873020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057449842
217 rdf:type schema:CreativeWork
218 https://doi.org/10.1056/nejmoa1611930 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084540243
219 rdf:type schema:CreativeWork
220 https://doi.org/10.1080/10408369891234273 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032196044
221 rdf:type schema:CreativeWork
222 https://doi.org/10.1089/10507250252949405 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059204304
223 rdf:type schema:CreativeWork
224 https://doi.org/10.1089/thy.2015.0140 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059322038
225 rdf:type schema:CreativeWork
226 https://doi.org/10.1093/ageing/afy169 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107246097
227 rdf:type schema:CreativeWork
228 https://doi.org/10.1096/fj.03-0428com schema:sameAs https://app.dimensions.ai/details/publication/pub.1030749751
229 rdf:type schema:CreativeWork
230 https://doi.org/10.1111/j.1365-2796.2011.02361.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1039182305
231 rdf:type schema:CreativeWork
232 https://doi.org/10.1113/jphysiol.2002.016832 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045081344
233 rdf:type schema:CreativeWork
234 https://doi.org/10.1146/annurev.bi.49.070180.003315 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047159530
235 rdf:type schema:CreativeWork
236 https://doi.org/10.1152/jappl.2000.89.1.176 schema:sameAs https://app.dimensions.ai/details/publication/pub.1074670958
237 rdf:type schema:CreativeWork
238 https://doi.org/10.1161/01.atv.10.4.497 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030639423
239 rdf:type schema:CreativeWork
240 https://doi.org/10.1161/01.atv.15.8.1086 schema:sameAs https://app.dimensions.ai/details/publication/pub.1063334079
241 rdf:type schema:CreativeWork
242 https://doi.org/10.1161/circgenetics.109.908905 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028594616
243 rdf:type schema:CreativeWork
244 https://doi.org/10.1161/circresaha.116.305085 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028405305
245 rdf:type schema:CreativeWork
246 https://doi.org/10.1161/hc5001.100795 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027663342
247 rdf:type schema:CreativeWork
248 https://doi.org/10.1194/jlr.m002717 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024123066
249 rdf:type schema:CreativeWork
250 https://doi.org/10.1194/jlr.m075432 schema:sameAs https://app.dimensions.ai/details/publication/pub.1086110994
251 rdf:type schema:CreativeWork
252 https://doi.org/10.1210/jc.2011-1444 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064292920
253 rdf:type schema:CreativeWork
254 https://doi.org/10.1210/jc.85.3.977 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064301325
255 rdf:type schema:CreativeWork
256 https://doi.org/10.1371/journal.pone.0112718 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026406969
257 rdf:type schema:CreativeWork
258 https://doi.org/10.1507/endocrj.k09e-359 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009740053
259 rdf:type schema:CreativeWork
260 https://doi.org/10.2739/kurumemedj.53.29 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031581694
261 rdf:type schema:CreativeWork
262 https://doi.org/10.3810/psm.2009.04.1678 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052057441
263 rdf:type schema:CreativeWork
264 https://doi.org/10.5551/jat.2337 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042487170
265 rdf:type schema:CreativeWork
266 https://doi.org/10.5551/jat.9.163 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010018448
267 rdf:type schema:CreativeWork
268 https://www.grid.ac/institutes/grid.256642.1 schema:alternateName Gunma University
269 schema:name Department of Clinical Laboratory Medicine, Gunma University Graduate School of Medicine, Maebashi, 371-8511, Japan.
270 Department of Clinical Laboratory Medicine, Gunma University Graduate School of Medicine, Maebashi, 371-8511, Japan. ktsune@gunma-u.ac.jp.
271 Faculty of Education, Ikuei University, Takasaki, 370-0011, Japan.
272 School of Medical Technology, Faculty of Health Science, Gunma Paz University, Takasaki, 370-0006, Japan.
273 rdf:type schema:Organization
274 https://www.grid.ac/institutes/grid.412200.5 schema:alternateName Nippon Sport Science University
275 schema:name Graduate School of Health and Sport Science, Nippon Sport Science University, Yokohama, 227-0033, Japan.
276 rdf:type schema:Organization
 




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


...