Fourier-transform-infrared-spectroscopy based spectral-biomarker selection towards optimum diagnostic differentiation of oral leukoplakia and cancer View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2015-10

AUTHORS

Satarupa Banerjee, Mousumi Pal, Jitamanyu Chakrabarty, Cyril Petibois, Ranjan Rashmi Paul, Amita Giri, Jyotirmoy Chatterjee

ABSTRACT

In search of specific label-free biomarkers for differentiation of two oral lesions, namely oral leukoplakia (OLK) and oral squamous-cell carcinoma (OSCC), Fourier-transform infrared (FTIR) spectroscopy was performed on paraffin-embedded tissue sections from 47 human subjects (eight normal (NOM), 16 OLK, and 23 OSCC). Difference between mean spectra (DBMS), Mann-Whitney's U test, and forward feature selection (FFS) techniques were used for optimising spectral-marker selection. Classification of diseases was performed with linear and quadratic support vector machine (SVM) at 10-fold cross-validation, using different combinations of spectral features. It was observed that six features obtained through FFS enabled differentiation of NOM and OSCC tissue (1782, 1713, 1665, 1545, 1409, and 1161 cm(-1)) and were most significant, able to classify OLK and OSCC with 81.3 % sensitivity, 95.7 % specificity, and 89.7 % overall accuracy. The 43 spectral markers extracted through Mann-Whitney's U Test were the least significant when quadratic SVM was used. Considering the high sensitivity and specificity of the FFS technique, extracting only six spectral biomarkers was thus most useful for diagnosis of OLK and OSCC, and to overcome inter and intra-observer variability experienced in diagnostic best-practice histopathological procedure. By considering the biochemical assignment of these six spectral signatures, this work also revealed altered glycogen and keratin content in histological sections which could able to discriminate OLK and OSCC. The method was validated through spectral selection by the DBMS technique. Thus this method has potential for diagnostic cost minimisation for oral lesions by label-free biomarker identification. More... »

PAGES

7935-7943

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00216-015-8960-3

DOI

http://dx.doi.org/10.1007/s00216-015-8960-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1040447617

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/26342309


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/2008/1004", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical Biotechnology", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/10", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Technology", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Biomarkers, Tumor", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Carcinoma, Squamous Cell", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Leukoplakia, Oral", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Mouth", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Mouth Neoplasms", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Sensitivity and Specificity", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Spectroscopy, Fourier Transform Infrared", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Support Vector Machine", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Indian Institute of Technology Kharagpur", 
          "id": "https://www.grid.ac/institutes/grid.429017.9", 
          "name": [
            "School of Medical Science and Technology, Indian Institute of Technology, 721302, Kharagpur, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Banerjee", 
        "givenName": "Satarupa", 
        "id": "sg:person.0735321325.93", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0735321325.93"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Department of Oral and Maxillofacial Pathology, Guru Nanak Institute of Dental Science and Research, 157/F Nilganj Road, Panihati, 700 114, Kolkata, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Pal", 
        "givenName": "Mousumi", 
        "id": "sg:person.0610042437.00", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0610042437.00"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Institute of Technology Durgapur", 
          "id": "https://www.grid.ac/institutes/grid.444419.8", 
          "name": [
            "Department of Chemistry, National Institute of Technology, 713209, Durgapur, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Chakrabarty", 
        "givenName": "Jitamanyu", 
        "id": "sg:person.0763236303.26", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0763236303.26"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Bordeaux", 
          "id": "https://www.grid.ac/institutes/grid.412041.2", 
          "name": [
            "University of Bordeaux \u2013 Inserm U1029 LAMC \u2013 Biophysics of Vascular Plasticity, 33608, Pessac, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Petibois", 
        "givenName": "Cyril", 
        "id": "sg:person.0613723320.30", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0613723320.30"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Department of Oral and Maxillofacial Pathology, Guru Nanak Institute of Dental Science and Research, 157/F Nilganj Road, Panihati, 700 114, Kolkata, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Paul", 
        "givenName": "Ranjan Rashmi", 
        "id": "sg:person.01040517437.95", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01040517437.95"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "North Bengal Medical College and Hospital", 
          "id": "https://www.grid.ac/institutes/grid.416411.7", 
          "name": [
            "Department of Pathology, North Bengal Medical College and Hospital, 734012, Darjeeling, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Giri", 
        "givenName": "Amita", 
        "id": "sg:person.010275311202.18", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010275311202.18"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Indian Institute of Technology Kharagpur", 
          "id": "https://www.grid.ac/institutes/grid.429017.9", 
          "name": [
            "School of Medical Science and Technology, Indian Institute of Technology, 721302, Kharagpur, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Chatterjee", 
        "givenName": "Jyotirmoy", 
        "id": "sg:person.01246277203.66", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01246277203.66"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.addr.2015.03.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000480879"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4137/bic.s12951", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001303079"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/(sici)1520-6343(1999)5:2<117::aid-bspy5>3.0.co;2-k", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005752091"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1039/c3an00256j", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008044405"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.oraloncology.2008.05.016", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012323208"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0030-4220(68)90437-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013527782"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0030-4220(68)90437-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013527782"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0304-3835(96)04450-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015421036"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1745-7270.2007.00320.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017684681"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1039/c2an35483g", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020634264"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/154411130301400105", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020876508"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/154411130301400105", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020876508"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/hed.23962", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024019656"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1472-6947-10-16", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027114800", 
          "https://doi.org/10.1186/1472-6947-10-16"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1039/c2an16300d", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029863020"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jbio.201300190", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031134214"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/jid.1955.82", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031633985", 
          "https://doi.org/10.1038/jid.1955.82"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1006/excr.1993.1185", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033990461"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nprot.2014.110", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034819774", 
          "https://doi.org/10.1038/nprot.2014.110"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1039/c2ay25544h", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035641215"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0116491", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036450390"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cdp.2003.11.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038523471"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/05704920701829043", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040216494"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/btt084", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041296281"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1096/fj.02-0752rev", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041814143"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/jid.1958.130", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047246942", 
          "https://doi.org/10.1038/jid.1958.130"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00216-006-0827-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048936592", 
          "https://doi.org/10.1007/s00216-006-0827-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00216-006-0827-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048936592", 
          "https://doi.org/10.1007/s00216-006-0827-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1385/bter:87:1-3:045", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048972841", 
          "https://doi.org/10.1385/bter:87:1-3:045"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00024382-199912000-00012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050444766"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00024382-199912000-00012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050444766"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1749-6632.1960.tb49965.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050527222"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0304-4165(91)90172-d", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052688489"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0304-4165(91)90172-d", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052688489"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1117/1.jbo.17.10.105002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052929323"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4028/www.scientific.net/amr.550-553.1304", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1072027226"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1078495556", 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2015-10", 
    "datePublishedReg": "2015-10-01", 
    "description": "In search of specific label-free biomarkers for differentiation of two oral lesions, namely oral leukoplakia (OLK) and oral squamous-cell carcinoma (OSCC), Fourier-transform infrared (FTIR) spectroscopy was performed on paraffin-embedded tissue sections from 47 human subjects (eight normal (NOM), 16 OLK, and 23 OSCC). Difference between mean spectra (DBMS), Mann-Whitney's U test, and forward feature selection (FFS) techniques were used for optimising spectral-marker selection. Classification of diseases was performed with linear and quadratic support vector machine (SVM) at 10-fold cross-validation, using different combinations of spectral features. It was observed that six features obtained through FFS enabled differentiation of NOM and OSCC tissue (1782, 1713, 1665, 1545, 1409, and 1161\u00a0cm(-1)) and were most significant, able to classify OLK and OSCC with 81.3\u00a0% sensitivity, 95.7\u00a0% specificity, and 89.7\u00a0% overall accuracy. The 43 spectral markers extracted through Mann-Whitney's U Test were the least significant when quadratic SVM was used. Considering the high sensitivity and specificity of the FFS technique, extracting only six spectral biomarkers was thus most useful for diagnosis of OLK and OSCC, and to overcome inter and intra-observer variability experienced in diagnostic best-practice histopathological procedure. By considering the biochemical assignment of these six spectral signatures, this work also revealed altered glycogen and keratin content in histological sections which could able to discriminate OLK and OSCC. The method was validated through spectral selection by the DBMS technique. Thus this method has potential for diagnostic cost minimisation for oral lesions by label-free biomarker identification. ", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s00216-015-8960-3", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1357342", 
        "issn": [
          "1618-2642", 
          "1618-2650"
        ], 
        "name": "Analytical and Bioanalytical Chemistry", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "26", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "407"
      }
    ], 
    "name": "Fourier-transform-infrared-spectroscopy based spectral-biomarker selection towards optimum diagnostic differentiation of oral leukoplakia and cancer", 
    "pagination": "7935-7943", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "c0acde10e1727a67ab61381a40608b58f168b25a413602daa6e1833900188448"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "26342309"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101134327"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s00216-015-8960-3"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1040447617"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s00216-015-8960-3", 
      "https://app.dimensions.ai/details/publication/pub.1040447617"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T15:13", 
    "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/v90/0000000001_0000000264/records_8663_00000592.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2Fs00216-015-8960-3"
  }
]
 

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.10.1007/s00216-015-8960-3'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00216-015-8960-3'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00216-015-8960-3'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00216-015-8960-3'


 

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

261 TRIPLES      21 PREDICATES      70 URIs      30 LITERALS      18 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s00216-015-8960-3 schema:about N1a6d185fbb504e51b59d6eca4a75aabb
2 N5eb2dc4aab3348a7a50882fa9028c165
3 Na1524dfd1c8743faaf3a7b2edb3e2c7e
4 Na4dfe9bb1aa040a89cccc7a261ea5072
5 Nb9d397de309c4c91b047f083b5094649
6 Nd6f193fe774f451ca37c4628df520832
7 Ndbf58c5a60324170bfcc75b37957c416
8 Ndc4749548026489d9226b9dee762d939
9 Nfdaed72d3fee4702b709c24b765581fb
10 anzsrc-for:10
11 anzsrc-for:1004
12 schema:author Nbea17323d20c4fe2bd59fd4c9dd8fe99
13 schema:citation sg:pub.10.1007/s00216-006-0827-1
14 sg:pub.10.1038/jid.1955.82
15 sg:pub.10.1038/jid.1958.130
16 sg:pub.10.1038/nprot.2014.110
17 sg:pub.10.1186/1472-6947-10-16
18 sg:pub.10.1385/bter:87:1-3:045
19 https://app.dimensions.ai/details/publication/pub.1078495556
20 https://doi.org/10.1002/(sici)1520-6343(1999)5:2<117::aid-bspy5>3.0.co;2-k
21 https://doi.org/10.1002/hed.23962
22 https://doi.org/10.1002/jbio.201300190
23 https://doi.org/10.1006/excr.1993.1185
24 https://doi.org/10.1016/0030-4220(68)90437-4
25 https://doi.org/10.1016/0304-4165(91)90172-d
26 https://doi.org/10.1016/j.addr.2015.03.009
27 https://doi.org/10.1016/j.cdp.2003.11.004
28 https://doi.org/10.1016/j.oraloncology.2008.05.016
29 https://doi.org/10.1016/s0304-3835(96)04450-3
30 https://doi.org/10.1039/c2an16300d
31 https://doi.org/10.1039/c2an35483g
32 https://doi.org/10.1039/c2ay25544h
33 https://doi.org/10.1039/c3an00256j
34 https://doi.org/10.1080/05704920701829043
35 https://doi.org/10.1093/bioinformatics/btt084
36 https://doi.org/10.1096/fj.02-0752rev
37 https://doi.org/10.1097/00024382-199912000-00012
38 https://doi.org/10.1111/j.1745-7270.2007.00320.x
39 https://doi.org/10.1111/j.1749-6632.1960.tb49965.x
40 https://doi.org/10.1117/1.jbo.17.10.105002
41 https://doi.org/10.1177/154411130301400105
42 https://doi.org/10.1371/journal.pone.0116491
43 https://doi.org/10.4028/www.scientific.net/amr.550-553.1304
44 https://doi.org/10.4137/bic.s12951
45 schema:datePublished 2015-10
46 schema:datePublishedReg 2015-10-01
47 schema:description In search of specific label-free biomarkers for differentiation of two oral lesions, namely oral leukoplakia (OLK) and oral squamous-cell carcinoma (OSCC), Fourier-transform infrared (FTIR) spectroscopy was performed on paraffin-embedded tissue sections from 47 human subjects (eight normal (NOM), 16 OLK, and 23 OSCC). Difference between mean spectra (DBMS), Mann-Whitney's U test, and forward feature selection (FFS) techniques were used for optimising spectral-marker selection. Classification of diseases was performed with linear and quadratic support vector machine (SVM) at 10-fold cross-validation, using different combinations of spectral features. It was observed that six features obtained through FFS enabled differentiation of NOM and OSCC tissue (1782, 1713, 1665, 1545, 1409, and 1161 cm(-1)) and were most significant, able to classify OLK and OSCC with 81.3 % sensitivity, 95.7 % specificity, and 89.7 % overall accuracy. The 43 spectral markers extracted through Mann-Whitney's U Test were the least significant when quadratic SVM was used. Considering the high sensitivity and specificity of the FFS technique, extracting only six spectral biomarkers was thus most useful for diagnosis of OLK and OSCC, and to overcome inter and intra-observer variability experienced in diagnostic best-practice histopathological procedure. By considering the biochemical assignment of these six spectral signatures, this work also revealed altered glycogen and keratin content in histological sections which could able to discriminate OLK and OSCC. The method was validated through spectral selection by the DBMS technique. Thus this method has potential for diagnostic cost minimisation for oral lesions by label-free biomarker identification.
48 schema:genre research_article
49 schema:inLanguage en
50 schema:isAccessibleForFree false
51 schema:isPartOf N4eb64b67d3064222b9e03cddbc1fe79c
52 Na7ca58c9e0d5421da55d8445a127486d
53 sg:journal.1357342
54 schema:name Fourier-transform-infrared-spectroscopy based spectral-biomarker selection towards optimum diagnostic differentiation of oral leukoplakia and cancer
55 schema:pagination 7935-7943
56 schema:productId N26f5abc6c90e444c9a7007a79c9793fd
57 N5e0aefe5d4154dcd80fbd09b5cd1db47
58 Nb94ce3d611b343c593ce9edc1cc46ad0
59 Nc7cf2cd36b814ac9a6f81fa55bc84529
60 Nfccb305cedfd41e29c74640084b260d8
61 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040447617
62 https://doi.org/10.1007/s00216-015-8960-3
63 schema:sdDatePublished 2019-04-10T15:13
64 schema:sdLicense https://scigraph.springernature.com/explorer/license/
65 schema:sdPublisher N43f1f0b5ccbc4fd9b2b9997c6ce86f6d
66 schema:url http://link.springer.com/10.1007%2Fs00216-015-8960-3
67 sgo:license sg:explorer/license/
68 sgo:sdDataset articles
69 rdf:type schema:ScholarlyArticle
70 N0fcd135c4b504475aca8bedc1d565cda schema:name Department of Oral and Maxillofacial Pathology, Guru Nanak Institute of Dental Science and Research, 157/F Nilganj Road, Panihati, 700 114, Kolkata, India
71 rdf:type schema:Organization
72 N1a6d185fbb504e51b59d6eca4a75aabb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
73 schema:name Carcinoma, Squamous Cell
74 rdf:type schema:DefinedTerm
75 N26f5abc6c90e444c9a7007a79c9793fd schema:name nlm_unique_id
76 schema:value 101134327
77 rdf:type schema:PropertyValue
78 N3ec6849d90424768bdf2c369c84c9e1d rdf:first sg:person.01040517437.95
79 rdf:rest N687a8ac6f20a4adf9007ffa6a19ae180
80 N43f1f0b5ccbc4fd9b2b9997c6ce86f6d schema:name Springer Nature - SN SciGraph project
81 rdf:type schema:Organization
82 N4eb64b67d3064222b9e03cddbc1fe79c schema:volumeNumber 407
83 rdf:type schema:PublicationVolume
84 N5a4ad527860549d0ad46233208c8f093 rdf:first sg:person.0613723320.30
85 rdf:rest N3ec6849d90424768bdf2c369c84c9e1d
86 N5e0aefe5d4154dcd80fbd09b5cd1db47 schema:name pubmed_id
87 schema:value 26342309
88 rdf:type schema:PropertyValue
89 N5eb2dc4aab3348a7a50882fa9028c165 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
90 schema:name Spectroscopy, Fourier Transform Infrared
91 rdf:type schema:DefinedTerm
92 N687a8ac6f20a4adf9007ffa6a19ae180 rdf:first sg:person.010275311202.18
93 rdf:rest N9be0482c9c8a4da8a8b0f1395e04afbc
94 N9be0482c9c8a4da8a8b0f1395e04afbc rdf:first sg:person.01246277203.66
95 rdf:rest rdf:nil
96 Na1524dfd1c8743faaf3a7b2edb3e2c7e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
97 schema:name Humans
98 rdf:type schema:DefinedTerm
99 Na4dfe9bb1aa040a89cccc7a261ea5072 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
100 schema:name Support Vector Machine
101 rdf:type schema:DefinedTerm
102 Na7ca58c9e0d5421da55d8445a127486d schema:issueNumber 26
103 rdf:type schema:PublicationIssue
104 Nb1db98ffbe1d4ba2a57333ea6aa45924 rdf:first sg:person.0610042437.00
105 rdf:rest Nd70fa572e44948d1b25ac4378c68a328
106 Nb94ce3d611b343c593ce9edc1cc46ad0 schema:name doi
107 schema:value 10.1007/s00216-015-8960-3
108 rdf:type schema:PropertyValue
109 Nb9d397de309c4c91b047f083b5094649 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
110 schema:name Mouth
111 rdf:type schema:DefinedTerm
112 Nbea17323d20c4fe2bd59fd4c9dd8fe99 rdf:first sg:person.0735321325.93
113 rdf:rest Nb1db98ffbe1d4ba2a57333ea6aa45924
114 Nc7cf2cd36b814ac9a6f81fa55bc84529 schema:name dimensions_id
115 schema:value pub.1040447617
116 rdf:type schema:PropertyValue
117 Nd6f193fe774f451ca37c4628df520832 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
118 schema:name Sensitivity and Specificity
119 rdf:type schema:DefinedTerm
120 Nd70fa572e44948d1b25ac4378c68a328 rdf:first sg:person.0763236303.26
121 rdf:rest N5a4ad527860549d0ad46233208c8f093
122 Ndbf58c5a60324170bfcc75b37957c416 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
123 schema:name Leukoplakia, Oral
124 rdf:type schema:DefinedTerm
125 Ndc4749548026489d9226b9dee762d939 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
126 schema:name Mouth Neoplasms
127 rdf:type schema:DefinedTerm
128 Nfccb305cedfd41e29c74640084b260d8 schema:name readcube_id
129 schema:value c0acde10e1727a67ab61381a40608b58f168b25a413602daa6e1833900188448
130 rdf:type schema:PropertyValue
131 Nfdaed72d3fee4702b709c24b765581fb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
132 schema:name Biomarkers, Tumor
133 rdf:type schema:DefinedTerm
134 Nfe521d399c9e42e994266db6c60de3ca schema:name Department of Oral and Maxillofacial Pathology, Guru Nanak Institute of Dental Science and Research, 157/F Nilganj Road, Panihati, 700 114, Kolkata, India
135 rdf:type schema:Organization
136 anzsrc-for:10 schema:inDefinedTermSet anzsrc-for:
137 schema:name Technology
138 rdf:type schema:DefinedTerm
139 anzsrc-for:1004 schema:inDefinedTermSet anzsrc-for:
140 schema:name Medical Biotechnology
141 rdf:type schema:DefinedTerm
142 sg:journal.1357342 schema:issn 1618-2642
143 1618-2650
144 schema:name Analytical and Bioanalytical Chemistry
145 rdf:type schema:Periodical
146 sg:person.010275311202.18 schema:affiliation https://www.grid.ac/institutes/grid.416411.7
147 schema:familyName Giri
148 schema:givenName Amita
149 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010275311202.18
150 rdf:type schema:Person
151 sg:person.01040517437.95 schema:affiliation N0fcd135c4b504475aca8bedc1d565cda
152 schema:familyName Paul
153 schema:givenName Ranjan Rashmi
154 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01040517437.95
155 rdf:type schema:Person
156 sg:person.01246277203.66 schema:affiliation https://www.grid.ac/institutes/grid.429017.9
157 schema:familyName Chatterjee
158 schema:givenName Jyotirmoy
159 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01246277203.66
160 rdf:type schema:Person
161 sg:person.0610042437.00 schema:affiliation Nfe521d399c9e42e994266db6c60de3ca
162 schema:familyName Pal
163 schema:givenName Mousumi
164 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0610042437.00
165 rdf:type schema:Person
166 sg:person.0613723320.30 schema:affiliation https://www.grid.ac/institutes/grid.412041.2
167 schema:familyName Petibois
168 schema:givenName Cyril
169 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0613723320.30
170 rdf:type schema:Person
171 sg:person.0735321325.93 schema:affiliation https://www.grid.ac/institutes/grid.429017.9
172 schema:familyName Banerjee
173 schema:givenName Satarupa
174 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0735321325.93
175 rdf:type schema:Person
176 sg:person.0763236303.26 schema:affiliation https://www.grid.ac/institutes/grid.444419.8
177 schema:familyName Chakrabarty
178 schema:givenName Jitamanyu
179 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0763236303.26
180 rdf:type schema:Person
181 sg:pub.10.1007/s00216-006-0827-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048936592
182 https://doi.org/10.1007/s00216-006-0827-1
183 rdf:type schema:CreativeWork
184 sg:pub.10.1038/jid.1955.82 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031633985
185 https://doi.org/10.1038/jid.1955.82
186 rdf:type schema:CreativeWork
187 sg:pub.10.1038/jid.1958.130 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047246942
188 https://doi.org/10.1038/jid.1958.130
189 rdf:type schema:CreativeWork
190 sg:pub.10.1038/nprot.2014.110 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034819774
191 https://doi.org/10.1038/nprot.2014.110
192 rdf:type schema:CreativeWork
193 sg:pub.10.1186/1472-6947-10-16 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027114800
194 https://doi.org/10.1186/1472-6947-10-16
195 rdf:type schema:CreativeWork
196 sg:pub.10.1385/bter:87:1-3:045 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048972841
197 https://doi.org/10.1385/bter:87:1-3:045
198 rdf:type schema:CreativeWork
199 https://app.dimensions.ai/details/publication/pub.1078495556 schema:CreativeWork
200 https://doi.org/10.1002/(sici)1520-6343(1999)5:2<117::aid-bspy5>3.0.co;2-k schema:sameAs https://app.dimensions.ai/details/publication/pub.1005752091
201 rdf:type schema:CreativeWork
202 https://doi.org/10.1002/hed.23962 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024019656
203 rdf:type schema:CreativeWork
204 https://doi.org/10.1002/jbio.201300190 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031134214
205 rdf:type schema:CreativeWork
206 https://doi.org/10.1006/excr.1993.1185 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033990461
207 rdf:type schema:CreativeWork
208 https://doi.org/10.1016/0030-4220(68)90437-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013527782
209 rdf:type schema:CreativeWork
210 https://doi.org/10.1016/0304-4165(91)90172-d schema:sameAs https://app.dimensions.ai/details/publication/pub.1052688489
211 rdf:type schema:CreativeWork
212 https://doi.org/10.1016/j.addr.2015.03.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000480879
213 rdf:type schema:CreativeWork
214 https://doi.org/10.1016/j.cdp.2003.11.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038523471
215 rdf:type schema:CreativeWork
216 https://doi.org/10.1016/j.oraloncology.2008.05.016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012323208
217 rdf:type schema:CreativeWork
218 https://doi.org/10.1016/s0304-3835(96)04450-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015421036
219 rdf:type schema:CreativeWork
220 https://doi.org/10.1039/c2an16300d schema:sameAs https://app.dimensions.ai/details/publication/pub.1029863020
221 rdf:type schema:CreativeWork
222 https://doi.org/10.1039/c2an35483g schema:sameAs https://app.dimensions.ai/details/publication/pub.1020634264
223 rdf:type schema:CreativeWork
224 https://doi.org/10.1039/c2ay25544h schema:sameAs https://app.dimensions.ai/details/publication/pub.1035641215
225 rdf:type schema:CreativeWork
226 https://doi.org/10.1039/c3an00256j schema:sameAs https://app.dimensions.ai/details/publication/pub.1008044405
227 rdf:type schema:CreativeWork
228 https://doi.org/10.1080/05704920701829043 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040216494
229 rdf:type schema:CreativeWork
230 https://doi.org/10.1093/bioinformatics/btt084 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041296281
231 rdf:type schema:CreativeWork
232 https://doi.org/10.1096/fj.02-0752rev schema:sameAs https://app.dimensions.ai/details/publication/pub.1041814143
233 rdf:type schema:CreativeWork
234 https://doi.org/10.1097/00024382-199912000-00012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050444766
235 rdf:type schema:CreativeWork
236 https://doi.org/10.1111/j.1745-7270.2007.00320.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1017684681
237 rdf:type schema:CreativeWork
238 https://doi.org/10.1111/j.1749-6632.1960.tb49965.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1050527222
239 rdf:type schema:CreativeWork
240 https://doi.org/10.1117/1.jbo.17.10.105002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052929323
241 rdf:type schema:CreativeWork
242 https://doi.org/10.1177/154411130301400105 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020876508
243 rdf:type schema:CreativeWork
244 https://doi.org/10.1371/journal.pone.0116491 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036450390
245 rdf:type schema:CreativeWork
246 https://doi.org/10.4028/www.scientific.net/amr.550-553.1304 schema:sameAs https://app.dimensions.ai/details/publication/pub.1072027226
247 rdf:type schema:CreativeWork
248 https://doi.org/10.4137/bic.s12951 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001303079
249 rdf:type schema:CreativeWork
250 https://www.grid.ac/institutes/grid.412041.2 schema:alternateName University of Bordeaux
251 schema:name University of Bordeaux – Inserm U1029 LAMC – Biophysics of Vascular Plasticity, 33608, Pessac, France
252 rdf:type schema:Organization
253 https://www.grid.ac/institutes/grid.416411.7 schema:alternateName North Bengal Medical College and Hospital
254 schema:name Department of Pathology, North Bengal Medical College and Hospital, 734012, Darjeeling, India
255 rdf:type schema:Organization
256 https://www.grid.ac/institutes/grid.429017.9 schema:alternateName Indian Institute of Technology Kharagpur
257 schema:name School of Medical Science and Technology, Indian Institute of Technology, 721302, Kharagpur, India
258 rdf:type schema:Organization
259 https://www.grid.ac/institutes/grid.444419.8 schema:alternateName National Institute of Technology Durgapur
260 schema:name Department of Chemistry, National Institute of Technology, 713209, Durgapur, India
261 rdf:type schema:Organization
 




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


...