First-in-human clinical study of novel technique to diagnose malignant melanoma via thermal conductivity measurements View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Takahiro Okabe, Taku Fujimura, Junnosuke Okajima, Yumi Kambayashi, Setsuya Aiba, Shigenao Maruyama

ABSTRACT

Melanoma is an aggressive skin cancer that originates from melanocytes and, especially in the case of early-stage melanoma, is distributed adjacent to the epidermis and superficial dermis. Although early-stage melanoma can be distinguished from benign nevus via a dermoscopy, it is difficult to distinguish invasive melanoma in its early stages from in situ melanoma. Because invasive melanoma must undergo a sentinel lymph node biopsy to be diagnosed, a non-invasive method to detect the micro-invasion of early-stage melanoma is needed for dermato-oncologists. This paper proposes a novel quantitative melanoma identification method based on accurate measurements of thermal conductivity using a pen-shaped device. This method requires skin temperature data for one minute to determine the effective thermal conductivity of the skin, allowing it to distinguish melanoma lesions from healthy skin. Results suggest that effective thermal conductivity was negative for in situ melanoma. However, in accordance with tumour progression, effective thermal conductivity was larger in invasive melanoma. The proposed thermal conductivity measurement is a novel tool that detects the micro-invasion of melanoma. More... »

PAGES

3853

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-019-40444-6

DOI

http://dx.doi.org/10.1038/s41598-019-40444-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112604245

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30846837


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/2008/1112", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Oncology and Carcinogenesis", 
        "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": "Hirosaki University", 
          "id": "https://www.grid.ac/institutes/grid.257016.7", 
          "name": [
            "Graduate School of Science and Technology, Hirosaki University, Hirosaki, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Okabe", 
        "givenName": "Takahiro", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tohoku University", 
          "id": "https://www.grid.ac/institutes/grid.69566.3a", 
          "name": [
            "Graduate School of Medicine, Tohoku University, Sendai, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fujimura", 
        "givenName": "Taku", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tohoku University", 
          "id": "https://www.grid.ac/institutes/grid.69566.3a", 
          "name": [
            "Institute of Fluid Science, Tohoku University, Sendai, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Okajima", 
        "givenName": "Junnosuke", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tohoku University", 
          "id": "https://www.grid.ac/institutes/grid.69566.3a", 
          "name": [
            "Graduate School of Medicine, Tohoku University, Sendai, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kambayashi", 
        "givenName": "Yumi", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tohoku University", 
          "id": "https://www.grid.ac/institutes/grid.69566.3a", 
          "name": [
            "Graduate School of Medicine, Tohoku University, Sendai, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Aiba", 
        "givenName": "Setsuya", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Institute Of Technology", 
          "id": "https://www.grid.ac/institutes/grid.482504.f", 
          "name": [
            "National Institute of Technology, Hachinohe College, Hachinohe, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Maruyama", 
        "givenName": "Shigenao", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1088/0957-0233/19/7/075104", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006581659"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0738-081x(95)00073-o", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022779026"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1524-4725.1981.tb00629.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038560461"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1524-4725.1981.tb00629.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038560461"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4684-8285-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039142765", 
          "https://doi.org/10.1007/978-1-4684-8285-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4684-8285-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039142765", 
          "https://doi.org/10.1007/978-1-4684-8285-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijthermalsci.2010.10.019", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049945158"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2147/ccid.s27902", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051700233"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1088/0031-9155/55/19/020", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059028364"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1088/0031-9155/55/19/020", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059028364"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijheatmasstransfer.2017.01.072", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083416012"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/1346-8138.13629", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085184782"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmoa1613210", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085917022"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/bjd.16098", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092412815"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/jdv.14782", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1100232088"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1001/jamadermatol.2018.0212", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1103422554"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijheatmasstransfer.2018.06.039", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1104593387"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11864-018-0560-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1105179185", 
          "https://doi.org/10.1007/s11864-018-0560-y"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-12", 
    "datePublishedReg": "2019-12-01", 
    "description": "Melanoma is an aggressive skin cancer that originates from melanocytes and, especially in the case of early-stage melanoma, is distributed adjacent to the epidermis and superficial dermis. Although early-stage melanoma can be distinguished from benign nevus via a dermoscopy, it is difficult to distinguish invasive melanoma in its early stages from in situ melanoma. Because invasive melanoma must undergo a sentinel lymph node biopsy to be diagnosed, a non-invasive method to detect the micro-invasion of early-stage melanoma is needed for dermato-oncologists. This paper proposes a novel quantitative melanoma identification method based on accurate measurements of thermal conductivity using a pen-shaped device. This method requires skin temperature data for one minute to determine the effective thermal conductivity of the skin, allowing it to distinguish melanoma lesions from healthy skin. Results suggest that effective thermal conductivity was negative for in situ melanoma. However, in accordance with tumour progression, effective thermal conductivity was larger in invasive melanoma. The proposed thermal conductivity measurement is a novel tool that detects the micro-invasion of melanoma.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1038/s41598-019-40444-6", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1045337", 
        "issn": [
          "2045-2322"
        ], 
        "name": "Scientific Reports", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "9"
      }
    ], 
    "name": "First-in-human clinical study of novel technique to diagnose malignant melanoma via thermal conductivity measurements", 
    "pagination": "3853", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "90b45d46f9bc95cb65b897ba61437493b17f2962ab43949f201667c2341e36fd"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30846837"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101563288"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/s41598-019-40444-6"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1112604245"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/s41598-019-40444-6", 
      "https://app.dimensions.ai/details/publication/pub.1112604245"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T11:25", 
    "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/v90/0000000356_0000000356/records_57865_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://www.nature.com/articles/s41598-019-40444-6"
  }
]
 

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.10.1038/s41598-019-40444-6'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-40444-6'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-40444-6'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-40444-6'


 

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

151 TRIPLES      21 PREDICATES      44 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/s41598-019-40444-6 schema:about anzsrc-for:11
2 anzsrc-for:1112
3 schema:author Nf65c11158c054eaa952e5337b0a73b79
4 schema:citation sg:pub.10.1007/978-1-4684-8285-0
5 sg:pub.10.1007/s11864-018-0560-y
6 https://doi.org/10.1001/jamadermatol.2018.0212
7 https://doi.org/10.1016/0738-081x(95)00073-o
8 https://doi.org/10.1016/j.ijheatmasstransfer.2017.01.072
9 https://doi.org/10.1016/j.ijheatmasstransfer.2018.06.039
10 https://doi.org/10.1016/j.ijthermalsci.2010.10.019
11 https://doi.org/10.1056/nejmoa1613210
12 https://doi.org/10.1088/0031-9155/55/19/020
13 https://doi.org/10.1088/0957-0233/19/7/075104
14 https://doi.org/10.1111/1346-8138.13629
15 https://doi.org/10.1111/bjd.16098
16 https://doi.org/10.1111/j.1524-4725.1981.tb00629.x
17 https://doi.org/10.1111/jdv.14782
18 https://doi.org/10.2147/ccid.s27902
19 schema:datePublished 2019-12
20 schema:datePublishedReg 2019-12-01
21 schema:description Melanoma is an aggressive skin cancer that originates from melanocytes and, especially in the case of early-stage melanoma, is distributed adjacent to the epidermis and superficial dermis. Although early-stage melanoma can be distinguished from benign nevus via a dermoscopy, it is difficult to distinguish invasive melanoma in its early stages from in situ melanoma. Because invasive melanoma must undergo a sentinel lymph node biopsy to be diagnosed, a non-invasive method to detect the micro-invasion of early-stage melanoma is needed for dermato-oncologists. This paper proposes a novel quantitative melanoma identification method based on accurate measurements of thermal conductivity using a pen-shaped device. This method requires skin temperature data for one minute to determine the effective thermal conductivity of the skin, allowing it to distinguish melanoma lesions from healthy skin. Results suggest that effective thermal conductivity was negative for in situ melanoma. However, in accordance with tumour progression, effective thermal conductivity was larger in invasive melanoma. The proposed thermal conductivity measurement is a novel tool that detects the micro-invasion of melanoma.
22 schema:genre research_article
23 schema:inLanguage en
24 schema:isAccessibleForFree true
25 schema:isPartOf N4773724834f747b1a0c1deaaeb3cd7ff
26 Ncb55f311a79e48febbc8faabfa7b8ba3
27 sg:journal.1045337
28 schema:name First-in-human clinical study of novel technique to diagnose malignant melanoma via thermal conductivity measurements
29 schema:pagination 3853
30 schema:productId N0d1319406a3246f7890012a3720a23d8
31 N0e1a566ac1b040f9b9a911eb2069eba3
32 N67998705f1c04e0a9c94545e898fb946
33 Nd89b388ad2724365ae100992d15898f8
34 Nf7ecba8b5d1943e4bc43d2bd73e5fc2e
35 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112604245
36 https://doi.org/10.1038/s41598-019-40444-6
37 schema:sdDatePublished 2019-04-11T11:25
38 schema:sdLicense https://scigraph.springernature.com/explorer/license/
39 schema:sdPublisher Nd5755d8eb31a4d348a2e219abe499225
40 schema:url https://www.nature.com/articles/s41598-019-40444-6
41 sgo:license sg:explorer/license/
42 sgo:sdDataset articles
43 rdf:type schema:ScholarlyArticle
44 N053435b755f94115a1779c7261bf4707 schema:affiliation https://www.grid.ac/institutes/grid.69566.3a
45 schema:familyName Kambayashi
46 schema:givenName Yumi
47 rdf:type schema:Person
48 N0892ac0463264dc1b48fc48ad3952cde schema:affiliation https://www.grid.ac/institutes/grid.257016.7
49 schema:familyName Okabe
50 schema:givenName Takahiro
51 rdf:type schema:Person
52 N0d1319406a3246f7890012a3720a23d8 schema:name dimensions_id
53 schema:value pub.1112604245
54 rdf:type schema:PropertyValue
55 N0e1a566ac1b040f9b9a911eb2069eba3 schema:name nlm_unique_id
56 schema:value 101563288
57 rdf:type schema:PropertyValue
58 N1b9bada6dc9f47a8a10321aa17993819 rdf:first Ne74e9e3c68234b98af63911b67578f5b
59 rdf:rest Nb52bd3a1595a49569c719f12d2334af7
60 N22f139f6d490491da2243d07d8db8a46 schema:affiliation https://www.grid.ac/institutes/grid.69566.3a
61 schema:familyName Fujimura
62 schema:givenName Taku
63 rdf:type schema:Person
64 N2e4bc11df46f471a9a84dbce79abde5b schema:affiliation https://www.grid.ac/institutes/grid.482504.f
65 schema:familyName Maruyama
66 schema:givenName Shigenao
67 rdf:type schema:Person
68 N4773724834f747b1a0c1deaaeb3cd7ff schema:volumeNumber 9
69 rdf:type schema:PublicationVolume
70 N67998705f1c04e0a9c94545e898fb946 schema:name doi
71 schema:value 10.1038/s41598-019-40444-6
72 rdf:type schema:PropertyValue
73 N767e93b4baf9433ab2a3e5d684456274 schema:affiliation https://www.grid.ac/institutes/grid.69566.3a
74 schema:familyName Aiba
75 schema:givenName Setsuya
76 rdf:type schema:Person
77 N9c25a4dd5584473080d3fbafb1076fd0 rdf:first N22f139f6d490491da2243d07d8db8a46
78 rdf:rest N1b9bada6dc9f47a8a10321aa17993819
79 Nb52bd3a1595a49569c719f12d2334af7 rdf:first N053435b755f94115a1779c7261bf4707
80 rdf:rest Nd2ac50e6874d404daaa2cb469e55913a
81 Ncb55f311a79e48febbc8faabfa7b8ba3 schema:issueNumber 1
82 rdf:type schema:PublicationIssue
83 Nd2ac50e6874d404daaa2cb469e55913a rdf:first N767e93b4baf9433ab2a3e5d684456274
84 rdf:rest Ne7c8e046df2a408f9653143fd545ba8b
85 Nd5755d8eb31a4d348a2e219abe499225 schema:name Springer Nature - SN SciGraph project
86 rdf:type schema:Organization
87 Nd89b388ad2724365ae100992d15898f8 schema:name pubmed_id
88 schema:value 30846837
89 rdf:type schema:PropertyValue
90 Ne74e9e3c68234b98af63911b67578f5b schema:affiliation https://www.grid.ac/institutes/grid.69566.3a
91 schema:familyName Okajima
92 schema:givenName Junnosuke
93 rdf:type schema:Person
94 Ne7c8e046df2a408f9653143fd545ba8b rdf:first N2e4bc11df46f471a9a84dbce79abde5b
95 rdf:rest rdf:nil
96 Nf65c11158c054eaa952e5337b0a73b79 rdf:first N0892ac0463264dc1b48fc48ad3952cde
97 rdf:rest N9c25a4dd5584473080d3fbafb1076fd0
98 Nf7ecba8b5d1943e4bc43d2bd73e5fc2e schema:name readcube_id
99 schema:value 90b45d46f9bc95cb65b897ba61437493b17f2962ab43949f201667c2341e36fd
100 rdf:type schema:PropertyValue
101 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
102 schema:name Medical and Health Sciences
103 rdf:type schema:DefinedTerm
104 anzsrc-for:1112 schema:inDefinedTermSet anzsrc-for:
105 schema:name Oncology and Carcinogenesis
106 rdf:type schema:DefinedTerm
107 sg:journal.1045337 schema:issn 2045-2322
108 schema:name Scientific Reports
109 rdf:type schema:Periodical
110 sg:pub.10.1007/978-1-4684-8285-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039142765
111 https://doi.org/10.1007/978-1-4684-8285-0
112 rdf:type schema:CreativeWork
113 sg:pub.10.1007/s11864-018-0560-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1105179185
114 https://doi.org/10.1007/s11864-018-0560-y
115 rdf:type schema:CreativeWork
116 https://doi.org/10.1001/jamadermatol.2018.0212 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103422554
117 rdf:type schema:CreativeWork
118 https://doi.org/10.1016/0738-081x(95)00073-o schema:sameAs https://app.dimensions.ai/details/publication/pub.1022779026
119 rdf:type schema:CreativeWork
120 https://doi.org/10.1016/j.ijheatmasstransfer.2017.01.072 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083416012
121 rdf:type schema:CreativeWork
122 https://doi.org/10.1016/j.ijheatmasstransfer.2018.06.039 schema:sameAs https://app.dimensions.ai/details/publication/pub.1104593387
123 rdf:type schema:CreativeWork
124 https://doi.org/10.1016/j.ijthermalsci.2010.10.019 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049945158
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1056/nejmoa1613210 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085917022
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1088/0031-9155/55/19/020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059028364
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1088/0957-0233/19/7/075104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006581659
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1111/1346-8138.13629 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085184782
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1111/bjd.16098 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092412815
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1111/j.1524-4725.1981.tb00629.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1038560461
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1111/jdv.14782 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100232088
139 rdf:type schema:CreativeWork
140 https://doi.org/10.2147/ccid.s27902 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051700233
141 rdf:type schema:CreativeWork
142 https://www.grid.ac/institutes/grid.257016.7 schema:alternateName Hirosaki University
143 schema:name Graduate School of Science and Technology, Hirosaki University, Hirosaki, Japan
144 rdf:type schema:Organization
145 https://www.grid.ac/institutes/grid.482504.f schema:alternateName National Institute Of Technology
146 schema:name National Institute of Technology, Hachinohe College, Hachinohe, Japan
147 rdf:type schema:Organization
148 https://www.grid.ac/institutes/grid.69566.3a schema:alternateName Tohoku University
149 schema:name Graduate School of Medicine, Tohoku University, Sendai, Japan
150 Institute of Fluid Science, Tohoku University, Sendai, Japan
151 rdf:type schema:Organization
 




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


...