Optical Based Surface Plasmon Resonance Sensor for the Detection of the Various Kind of Cancerous Cell

This research explores a novel biosensor design that exhibits much higher sensitivity compared to conventional biosensors. The biosensor's uniqueness originated from its innovative structure, which incorporates N-FK51A/Ag/AlON/BlueP materials, as well as its cutting-edge fabrication method. The...

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Published inCell biochemistry and biophysics
Main Authors Rafi, Shah Ali, Emon, Wahiduzzaman, Rafsan, Ahmed Afif, Mahmud, Russel Reza, Nayan, Md Faysal, Eid, Mahmoud M A, Rashed, Ahmed Nabih Zaki
Format Journal Article
LanguageEnglish
Published United States 11.09.2024
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Summary:This research explores a novel biosensor design that exhibits much higher sensitivity compared to conventional biosensors. The biosensor's uniqueness originated from its innovative structure, which incorporates N-FK51A/Ag/AlON/BlueP materials, as well as its cutting-edge fabrication method. The refractive index component was considered when designing the SPR biosensor, which was developed from the angular analysis of the attenuated total reflection (ATR) approach for cancer detection. For instance, the resonance angle shifts by 15.57 deg when the refractive index changes from 1.360 to 1.401, demonstrating the sensor's responsiveness to variation in the refractive index. The sensitivities for skin (basal), cervical (HeLa), blood (Jurkat), adrenal gland (PC12), and breast (MDA-MB-231 and MCF-7) cancer cells were 197.65, 243.66, 255.36, 302.71, 372.57, and 416.85 deg/RIU, respectively. Also, the detection accuracy (DA), the figure of merit (FoM), and the quality factor were 0.37/deg, 155.94 (deg/RIU), and 26.71 RIU . We also examine the effects of substituting the noble, dielectric, 2D material layer with conventional biosensor materials for six cancers. Each time, the Ag/AION/BlueP layered structure performed best in distinguishing cancer cells from healthy cells. We also study the prism effects. The proposed biosensor, with a RI of 1.29-1.40, has a linear regression coefficient of R of 0.96094.
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ISSN:1085-9195
1559-0283
1559-0283
DOI:10.1007/s12013-024-01503-6