RESUMO
Melanoma is a destructive skin disease with few therapeutic options in the developed stage and therefore there is a critical need for reliable biomarkers for early diagnosis. In this context, microRNAs could play an important role as diagnostic biomarkers. Three datasets with accession numbers GSE31568, GSE61741 and GSE20994 were downloaded from the Gene Expression Omnibus (GEO) database. MATLAB software was used to analyze differentially expressed miRNAs between cutaneous melanoma plasma samples and normal plasma samples (control). Plasma levels of miR-193b, miR-146b-3p and miR-483-3p were evaluated by the RT-PCR method. Furthermore, linear regression followed by receiver operating characteristic analyses was performed to estimate whether selected plasma miRNAs were able to distinguish between cases and controls. Finally, the data were analyzed by unpaired Mann-Whitney U test using Graph pad prism 8 computer software. Specifically, miR-193b and miR-146b-3p were downregulated in the plasma of melanoma patients compared with control groups which were decreased 5 × [Formula: see text]-fold in miR-193b and 58-fold in miR-146b-3p, while miR-483-3p was upregulated 3.5-fold. After receiver operating characteristic (ROC) curve analysis, miR-193b with the most area under the curve (AUC: 1.00, 95% confidence interval 1.00-1.00, p < 0.0001) had the best discriminatory power, and miR-146b-3p had the large area under the curve (AUC: 0.96, 95% confidence interval 0.96-1.00, p < 0.0001) and consequently the high discriminatory power. Between these three miRNAs, miR-193b and miR-146b-3p had a high capacity to distinguish between melanoma patients and control groups that are appropriate to be applied in melanoma diagnosis as an early and noninvasive method.
RESUMO
Pesticides, widely used in modern agriculture, could potentially cause environmental pollution and affect human lives. Hence, the development of a highly sensitive sensing element to detect pesticide residues is crucial for food safety and ecosystem protection. Optical methods based on fluorescence properties provide an ideal approach for screening and quantification of these compounds in different medias including water, plant, and nutritional products. The development of fluorescence emitting carbon dot-based sensors for monitoring pesticides has attracted great attention in recent years. In comparison to other fluorophores, carbon dots have more promising optical features, higher quantum yields and better biocompatibility. This article aims to present a novel fluorescent sensing method of diazinon, glyphosate, and amicarbazone using plant-based carbon dots. A comprehensive characterization of carbon dots obtained from cauliflower was performed by methods including UV-visible, FTIR spectroscopy, fluorometry, AFM, DLS, and zeta sizer. Following this step, carbon dots were used to detect pesticides. The fluorescence quenching property of carbon dots has been utilized to identify detection limit of 0.25, 0.5, and 2 ng ml-1 for diazinon, amicarbazone, and glyphosate, respectively. Also, real sample study revealed that the detection of pesticides accompanied by our developed nano-sensor is repeatable and accurate. According to carbon dots specificity determination, the prepared nano sensor does not have the potential to identify "bromacil" and "dialen super" pesticides but the other three mentioned pesticides are detectable. The results confirm that synthesized green carbon dots are well qualified for application in food safety and environmental monitoring.
