Specimen For Detecting Infiltrative Large Intestine Tumors


Ontology type: sgo:Patent     


Patent Info

DATE

2012-07-04T00:00

AUTHORS

TOYOTA, MINORU , YAMAMOTO, EIICHIRO , KAMIMAE, SEIKO , SUZUKI, HIROMU , YAMANO, HIROO

ABSTRACT

Provided is a method for non-invasively obtaining an index for diagnosing the infiltration or invasive depth of a large intestine tumor. The method is characterized in that a specimen by which the infiltrative large intestine tumor can be detected is obtained by spraying a cleaning solvent onto the target large intestine mucous layer to separate the mucous from said mucous layer, and recovering the separated mucous along with the cleaning solvent. More... »

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/2008/2844", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "name": "TOYOTA, MINORU", 
        "type": "Person"
      }, 
      {
        "name": "YAMAMOTO, EIICHIRO", 
        "type": "Person"
      }, 
      {
        "name": "KAMIMAE, SEIKO", 
        "type": "Person"
      }, 
      {
        "name": "SUZUKI, HIROMU", 
        "type": "Person"
      }, 
      {
        "name": "YAMANO, HIROO", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1111/j.1572-0241.1999.00868.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003945786", 
          "https://doi.org/10.1111/j.1572-0241.1999.00868.x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1111/j.1572-0241.1999.00868.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003945786", 
          "https://doi.org/10.1111/j.1572-0241.1999.00868.x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/gut.38.3.365", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030231017"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1158/1940-6207.capr-10-0214", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050637987"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0140-6736(04)16002-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051346566"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/1354750021000042268", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058382662"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2012-07-04T00:00", 
    "description": "

Provided is a method for non-invasively obtaining an index for diagnosing the infiltration or invasive depth of a large intestine tumor. The method is characterized in that a specimen by which the infiltrative large intestine tumor can be detected is obtained by spraying a cleaning solvent onto the target large intestine mucous layer to separate the mucous from said mucous layer, and recovering the separated mucous along with the cleaning solvent.

", "id": "sg:patent.EP-2472257-A1", "keywords": [ "large intestine", "method", "non-invasively", "index", "infiltration", "depth", "specimen", "cleaning", "layer" ], "name": "SPECIMEN FOR DETECTING INFILTRATIVE LARGE INTESTINE TUMORS", "recipient": [ { "id": "https://www.grid.ac/institutes/grid.263171.0", "type": "Organization" } ], "sameAs": [ "https://app.dimensions.ai/details/patent/EP-2472257-A1" ], "sdDataset": "patents", "sdDatePublished": "2019-04-18T10:09", "sdLicense": "https://scigraph.springernature.com/explorer/license/", "sdPublisher": { "name": "Springer Nature - SN SciGraph project", "type": "Organization" }, "sdSource": "s3://com-uberresearch-data-patents-target-20190320-rc/data/sn-export/402f166718b70575fb5d4ffe01f064d1/0000100128-0000352499/json_export_00363.jsonl", "type": "Patent" } ]
 

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/patent.EP-2472257-A1'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/patent.EP-2472257-A1'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/patent.EP-2472257-A1'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/patent.EP-2472257-A1'


 

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

63 TRIPLES      15 PREDICATES      28 URIs      17 LITERALS      2 BLANK NODES

Subject Predicate Object
1 sg:patent.EP-2472257-A1 schema:about anzsrc-for:2844
2 schema:author N10d2f06ec472405594d53f64fbefe8c3
3 schema:citation sg:pub.10.1111/j.1572-0241.1999.00868.x
4 https://doi.org/10.1016/s0140-6736(04)16002-9
5 https://doi.org/10.1080/1354750021000042268
6 https://doi.org/10.1136/gut.38.3.365
7 https://doi.org/10.1158/1940-6207.capr-10-0214
8 schema:datePublished 2012-07-04T00:00
9 schema:description <p num="pa01">Provided is a method for non-invasively obtaining an index for diagnosing the infiltration or invasive depth of a large intestine tumor. The method is <b>characterized in that</b> a specimen by which the infiltrative large intestine tumor can be detected is obtained by spraying a cleaning solvent onto the target large intestine mucous layer to separate the mucous from said mucous layer, and recovering the separated mucous along with the cleaning solvent.<img id="iaf01" file="imgaf001.tif" wi="43" he="95" img-content="drawing" img-format="tif"/></p>
10 schema:keywords cleaning
11 depth
12 index
13 infiltration
14 large intestine
15 layer
16 method
17 non-invasively
18 specimen
19 schema:name SPECIMEN FOR DETECTING INFILTRATIVE LARGE INTESTINE TUMORS
20 schema:recipient https://www.grid.ac/institutes/grid.263171.0
21 schema:sameAs https://app.dimensions.ai/details/patent/EP-2472257-A1
22 schema:sdDatePublished 2019-04-18T10:09
23 schema:sdLicense https://scigraph.springernature.com/explorer/license/
24 schema:sdPublisher N2e54caaa8adb4321819a61555ef77ba0
25 sgo:license sg:explorer/license/
26 sgo:sdDataset patents
27 rdf:type sgo:Patent
28 N10d2f06ec472405594d53f64fbefe8c3 rdf:first N5d411551cf7a42859fe33487fb0cb56a
29 rdf:rest Nab1d7f47edf547e6b0471e63991bf776
30 N2e54caaa8adb4321819a61555ef77ba0 schema:name Springer Nature - SN SciGraph project
31 rdf:type schema:Organization
32 N5bfd4f9c43cf41e2874408b742b41324 rdf:first Ne5874e1bf4444e96a4a152cccfb4a8d0
33 rdf:rest Ncada6d96260e4aad90b46607fc8664a5
34 N5d411551cf7a42859fe33487fb0cb56a schema:name TOYOTA, MINORU
35 rdf:type schema:Person
36 N839deccc7f4a43a49be680d2db6c9dc5 schema:name SUZUKI, HIROMU
37 rdf:type schema:Person
38 Na54d94f9455d42999aded5dd501a879f schema:name YAMAMOTO, EIICHIRO
39 rdf:type schema:Person
40 Nab1d7f47edf547e6b0471e63991bf776 rdf:first Na54d94f9455d42999aded5dd501a879f
41 rdf:rest N5bfd4f9c43cf41e2874408b742b41324
42 Ncada6d96260e4aad90b46607fc8664a5 rdf:first N839deccc7f4a43a49be680d2db6c9dc5
43 rdf:rest Ne45b26e9f18e4a54913cc80f177710a3
44 Ne45b26e9f18e4a54913cc80f177710a3 rdf:first Nf3ee25eacfaa45cd9ca26e06909a428e
45 rdf:rest rdf:nil
46 Ne5874e1bf4444e96a4a152cccfb4a8d0 schema:name KAMIMAE, SEIKO
47 rdf:type schema:Person
48 Nf3ee25eacfaa45cd9ca26e06909a428e schema:name YAMANO, HIROO
49 rdf:type schema:Person
50 anzsrc-for:2844 schema:inDefinedTermSet anzsrc-for:
51 rdf:type schema:DefinedTerm
52 sg:pub.10.1111/j.1572-0241.1999.00868.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1003945786
53 https://doi.org/10.1111/j.1572-0241.1999.00868.x
54 rdf:type schema:CreativeWork
55 https://doi.org/10.1016/s0140-6736(04)16002-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051346566
56 rdf:type schema:CreativeWork
57 https://doi.org/10.1080/1354750021000042268 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058382662
58 rdf:type schema:CreativeWork
59 https://doi.org/10.1136/gut.38.3.365 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030231017
60 rdf:type schema:CreativeWork
61 https://doi.org/10.1158/1940-6207.capr-10-0214 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050637987
62 rdf:type schema:CreativeWork
63 https://www.grid.ac/institutes/grid.263171.0 schema:Organization
 




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


...