Altın Nanopartiküller Kullanılarak Kortizol İçin Plazmonik Sensör Sinyalinin Seçici Yükseltilmesi
Yılmaz, Gaye Ezgi
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Cortisol is a steroid hormone released by the human body in response to psychological and physiological stress. Cortisol can affect almost every organ system such as nervous, immune, cardiovascular, respiratory, reproductive, musculoskeletal, and covering systems. Besides, cortisol is a biomarker for numerous diseases and plays an important role in regulating various physiological processes such as blood pressure, glucose levels and carbohydrate metabolism. It also plays an important role in homeostasis of the cardiovascular, immune, renal, skeletal and endocrine systems. The health effects of cortisol depend on how often the hormone circulates in the body. High or low level amount of cortisol production can cause various diseases in the body. Therefore, it is very important to develop an effective, sensitive and selective method for the detection of cortisol. In this study, a plasmonic sensor that can detect cortisol from artificial plasma, artificial urine and aqueous solutions with high sensitivity and selectivity was designed by using a combination of plasmonic sensor, molecular imprinting method and gold nanoparticles. With this purpose; Three plasmonic sensors were prepared: cortisol imprinted N-metacroyl-(L)histidine methyl ester-gold nanoparticles- MIP-AuNP, NIP-AuNP prepared with the same recipe without cortisol imprinting and also cortisol imprinted MIP prepared with the same recipe without adding gold nanoparticles. After the size determination of the gold nanoparticles, each prepared plasmonic sensor was characterized by AFM, contact angle and FTIR-ATR spectrometry analyses. Concentration analyzes were performed with the MIP plasmonic sensor prepared without adding gold nanoparticles and the AuNP-MIP plasmonic sensor in order to examine the mechanism of action of AuNPs added to the structure in order to increase the plasmonic sensor response. In the light of the data obtained, it was observed that while the AuNP-MIP plasmonic sensor was able to analyze in real time with a correlation coefficient of 0.9744 between 0.01-100 ppb cortisol concentrations, the MIP plasmonic sensor was able to analyze in real time with a correlation coefficient of 0.9862 between 1-100 ppb cortisol concentrations. The LOD and LOQ values of the AuNP-MIP plasmonic sensor were calculated as 0.0082 and 0.027, and it was seen that the cortisol adsorpsion onto the AuNP-MIP plasmonic sensor fit to the Langmuir adsorption isotherm model. In addition, selectivity experiments were performed with AuNP-MIP, MIP and AuNP-NIP plasmonic sensors using clobetasol and fluticasone selected as competitor agents, and it was found that the AuNP-MIP plasmonic sensor was 6.26 and 6.11 times more selective than clobetasol and fluticasone, respectively. Also, the same competitor agents were applied to the AuNP-MIP and AuNP-NIP plasmonic sensors to determine the imprinting efficiency, and it was observed that the AuNP-MIP plasmonic sensor was 4.96 and 4.71 times more selective to the cortisol molecule than the AuNP-NIP plasmonic sensor. It was concluded that the AuNP-MIP plasmonic sensor was able to detect cortisol without any loss of performance in five consecutive reusability analysis. In addition, it has been observed that the AuNP-MIP plasmonic sensor can detect cortisol not only in aqueous media but also in complex media such as artificial plasma and artificial urine. Validation experiments were performed with high performance liquid chromatography (HPLC) studies.