Development of a SERS based cancer diagnosis approach employing cryosectioned thyroid tissue samples on PDMS

dc.authoridmert, sevda/0000-0002-0481-2829
dc.authorscopusid56592645900
dc.authorscopusid35190979600
dc.authorscopusid57207541140
dc.authorscopusid57221544109
dc.authorscopusid12797664300
dc.authorscopusid6701474288
dc.authorscopusid6701474288
dc.contributor.authorMert, Sevda
dc.contributor.authorSancak, Seda
dc.contributor.authorAydin, Hasan
dc.contributor.authorFersahoglu, Ayse Tuba
dc.contributor.authorSomay, Adnan
dc.contributor.authorOzkan, Ferda
dc.contributor.authorCulha, Mustafa
dc.contributor.otherGenetik ve Biyomühendislik / Genetic and Bio-Engineering
dc.date.accessioned2024-05-25T11:25:23Z
dc.date.available2024-05-25T11:25:23Z
dc.date.issued2022
dc.departmentOkan Universityen_US
dc.department-temp[Mert, Sevda] Yeditepe Univ, Fac Engn, Dept Genet & Bioengn, TR-34755 Istanbul, Turkey; [Mert, Sevda] Istanbul Okan Univ, Fac Engn, Dept Genet & Bioengn, TR-34959 Istanbul, Turkey; [Sancak, Seda] Univ Hlth Sci, Faith Sultan Mehmet Educ & Res Hosp, Dept Internal Med Endocrinol & Metab Disorders, TR-34752 Istanbul, Turkey; [Aydin, Hasan] Yeditepe Univ Hosp, Dept Internal Med, Sect Endocrinol & Metab, TR-34752 Istanbul, Turkey; [Fersahoglu, Ayse Tuba] Univ Hlth Sci, Fatih Sultan Melunet Educ & Res Hosp, Gen Surg Clin, TR-34752 Istanbul, Turkey; [Somay, Adnan] Univ Hlth Sci, Fatih Sultan Mehmet Educ & Res Hosp, Dept Pathol, TR-34752 Istanbul, Turkey; [Ozkan, Ferda] Yeditepe Univ Hosp, Dept Pathol, TR-34752 Istanbul, Turkey; [Culha, Mustafa] Oregon Hlth & Sci Univ, Canc Early Detect Adv Res Ctr CEDAR, Knight Canc Inst, Portland, OR 97239 USA; [Culha, Mustafa] Sabanci Univ, Nanotechnol Res & Applicat Ctr SUNUM, TR-34956 Istanbul, Turkey; [Culha, Mustafa] Augusta Univ, Dept Chem & Phys, Augusta, GA 30912 USAen_US
dc.descriptionmert, sevda/0000-0002-0481-2829en_US
dc.description.abstractAn efficient SERS based novel analytical approach named Cryosectioned-PDMS was developed systematically and evaluated applying on 64 thyroid biopsy samples. To utilize thyroid biopsy samples, a 20-mu l volume of h-AgNPs suspension was dropped on a 5-mu m thick cryosectioned biopsy specimen placed on the PDMS coated glass slide. The SERS spectra from a 10 x 10 points array acquired by mapping 22.5 mu m x 22.5 mu m sized area from suspended dried droplets placed on the tissue surface. The probability of correctly predicted performance for diagnosis of malignant, benign and healthy tissues was resulted in the accuracy of 100 % for the spectral bands at 667, 724, 920, 960, 1052, 1096, 1315 and 1457 cm(-1) using PCA-fed LDA machine learning. The Cryosectioned-PDMS biophotonic approach with PCA-LDA predictive model demonstrated that the vibrational signatures can accurately recognize the fingerprint of cancer pathology from a healthy one with a simple and fast sample preparation methodology. (C) 2022 Elsevier Inc. All rights reserved.en_US
dc.identifier.citation9
dc.identifier.doi10.1016/j.nano.2022.102577
dc.identifier.issn1549-9634
dc.identifier.issn1549-9642
dc.identifier.pmid35716872
dc.identifier.scopus2-s2.0-85132835581
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.nano.2022.102577
dc.identifier.urihttps://hdl.handle.net/20.500.14517/895
dc.identifier.volume44en_US
dc.identifier.wosWOS:000829546200003
dc.identifier.wosqualityQ2
dc.institutionauthorMert, Sevda
dc.language.isoen
dc.publisherElsevieren_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectSurface-enhanced Raman scattering biosensoren_US
dc.subjectCancer diagnosisen_US
dc.subjectCryosectioned-polydimethylsiloxane approachen_US
dc.subjectPrinciple component analysisen_US
dc.subjectLinear discriminant analysisen_US
dc.titleDevelopment of a SERS based cancer diagnosis approach employing cryosectioned thyroid tissue samples on PDMSen_US
dc.typeArticleen_US
dspace.entity.typePublication
relation.isAuthorOfPublication8029f7b7-87d8-4323-aded-80dea355ad32
relation.isAuthorOfPublication.latestForDiscovery8029f7b7-87d8-4323-aded-80dea355ad32
relation.isOrgUnitOfPublication2b8689c6-2a28-45db-b81c-7f828c944e77
relation.isOrgUnitOfPublication.latestForDiscovery2b8689c6-2a28-45db-b81c-7f828c944e77

Files