Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Review Citation - WoS: 116Citation - Scopus: 125Salivary Biomarkers: Novel Noninvasive Tools To Diagnose Chronic Inflammation(Springer, 2023) Dongiovanni, Paola; Meroni, Marica; Casati, Sara; Goldoni, Riccardo; Thomaz, Douglas Vieira; Kehr, Nermin Seda; Galimberti, DanielaSeveral chronic disorders including type 2 diabetes (T2D), obesity, heart disease and cancer are preceded by a state of chronic low-grade inflammation. Biomarkers for the early assessment of chronic disorders encompass acute phase proteins (APP), cytokines and chemokines, pro-inflammatory enzymes, lipids and oxidative stress mediators. These substances enter saliva through the blood flow and, in some cases, there is a close relation between their salivary and serum concentration. Saliva can be easily collected and stored with non-invasive and cost-saving procedures, and it is emerging the concept to use it for the detection of inflammatory biomarkers. To this purpose, the present review aims to discuss the advantages and challenges of using standard and cutting-edge techniques to discover salivary biomarkers which may be used in diagnosis/therapy of several chronic diseases with inflammatory consequences with the pursuit to possibly replace conventional paths with detectable soluble mediators in saliva. Specifically, the review describes the procedures used for saliva collection, the standard approaches for the measurement of salivary biomarkers and the novel methodological strategies such as biosensors to improve the quality of care for chronically affected patients.Article Citation - WoS: 9Citation - Scopus: 9Rapid Identification of Phosphorus Containing Proteins in Electrophoresis Gel Spots by Laser-Induced Breakdown Spectroscopy, Libs(Royal Society of Chemistry, 2014) Aras, Nadir; Yalçın, ŞerifeA novel method for the rapid in-gel identification of phosphorus containing proteins, specifically casein and ovalbumin, prior to mass spectrometric analysis for the elucidation of phosphorylation sites was developed. After polyacrylamide gel-electrophoretic separation, staining and drying, protein bands were subjected to focused laser pulses at the center or the vicinity of the protein band. Phosphorus containing proteins were recognized from their prominent phosphorus lines in the luminous plasma formed by energetic laser pulses. The LIBS emission intensity of phosphorus lines at 253.5 nm and 255.3 nm has been optimized with respect to laser energy and detector timing parameters by using pure casein in the pellet form. The method was applied to casein, ovalbumin, two commercially available standard protein mixtures and proteins extracted from the canola plant. It was shown that LIBS was capable of identifying phosphorus containing proteins directly in the gel matrix in nanogram amounts. Mass spectrometric analysis of the ovalbumin spot after the in-gel digestion procedure has proved the accuracy of the technique. With the speed and spatial resolution that LIBS offers, this technique shows promise in the micro-local spotting of phosphorus containing proteins in the polyacrylamide gel matrix prior to MS analysis for the determination of the phosphorylation sites. © 2014 The Royal Society of Chemistry.Article Citation - WoS: 8Citation - Scopus: 8Genetic Multivariate Calibration for Near Infrared Spectroscopic Determination of Protein, Moisture, Dry Mass, Hardness and Other Residues of Wheat(John Wiley and Sons Inc., 2006) Özdemir, DurmuşDetermination of wheat flour quality parameters, such as protein, moisture, dry mass by wet chemistry analyses takes long time. Near infrared spectroscopy (NIR) coupled with multivariate calibration offers a fast and nondestructive alternative to obtain reliable results. However, due to the complexity of the spectra obtained from NIR, some wavelength selection is generally required to improve the predictive ability of multivariate calibration methods. In this study, two different wheat data sets are investigated with the aim of establishing successful calibration models using NIR spectra of wheat samples. The first data set (material 1) was obtained from the ftp address (ftp://ftp.clarkson.edu/pub/hopkepk/Chemdata/) and contained 100 NIR spectra of wheat of which wet chemical analysis of protein and moisture content were done with reference methods. The second data set (material 2) contained 176 spectra and was downloaded from http://www.spectroscopynow.com/Spy/basehtml/SpyH/1,1181, 2-1-2-0-0-newsdetail-0-74,00.html. This wheat data set was given with the quality parameters, such as protein content, moisture content, other residues, dry mass, protein content in dry mass and hardness that were determined previously. Multivariate calibration models generated with genetic inverse least squares method demonstrated very good prediction results for the parameter mentioned here. Overall, the average per cent recoveries (APR) ranged between 99.23% and 100.34% with a standard deviation (SD) ranging from 0.34 to 3.15 for all the parameters investigated, except hardness. The APR value of hardness was 103.32 with the SD of 14.97.