Assessment of the Susceptibility of Aesthetic Orthodontic Brackets to Discoloration

The high aesthetic value of orthodontic appliance elements during treatment constitutes an important factor for an increasing number of adult patients. The aim of this study was to determine whether food dyes could significantly affect the color of both plastic and ceramic orthodontic brackets. Four brands of orthodontic brackets were investigated in the present study. Twenty-five samples of each kind were prepared. Five brackets of each series were stored in pure water, coffee, black tea and red wine for 1 h, 24 h, 7 days and 14 days. Total color change ΔE* of the samples was analyzed after storage with the use of the SpectroShade dental spectrophotometer (MHT, Verona, Italy) according to the CIE L*a*b* color scale. Correlations between bracket brand, kind of food dye and intensity of color change at the significance level p = 0.05 were investigated. After 1 and 24 h of incubation, water had the least influence on the color change of aesthetic orthodontic brackets, and tea had the greatest effect (p = 0.05). After 7 and 14 days of incubation of the samples, water still remained the environment influencing ΔE* change to the smallest extent, whereas storage in red wine changed the color of brackets to the significantly (p = 0.05) highest degree. The degree of discoloration of the assessed brackets depended on the type of material and the storage time in the environment of the individual food dyes (p = 0.05). The results of the present study show that, in the event of contact with food dyes, aesthetic orthodontic brackets discolor, the intensity of which can be influenced by the materials they are made of, the kind of food dye and the time of samples’ storage

Diagnostic Performance of Circulating miRNAs and Extracellular Vesicles in Acute Ischemic Stroke

Background: Increased inflammation activates blood coagulation system, higher platelet activation plays a key role in the pathophysiology of ischemic stroke (IS). During platelet activation and aggregation process, platelets may cause increased release of several proinflammatory, and prothrombotic mediators, including microRNAs (miRNAs) and extracellular vesicles (EVs). In the current study we aimed to assess circulating miRNAs profile related to platelet function and inflammation and circulating EVs from platelets, leukocytes, and endothelial cells to analyse their diagnostic and predictive utility in patients with acute IS. Methods: The study population consisted of 28 patients with the diagnosis of the acute IS. The control group consisted of 35 age- and gender-matched patients on acetylsalicylic acid (ASA) therapy without history of stroke and/or TIA with established stable coronary artery disease (CAD) and concomitant cardiovascular risk factors. Venous blood samples were collected from the control group and patients with IS on ASA therapy (a) 24 h after onset of acute IS, (b) 7-days following index hospitalization. Flow cytometry was used to determine the concentration of circulating EVs subtypes (from platelets, leukocytes, and endothelial cells) in platelet-depleted plasma and qRT-PCR was used to determine several circulating plasma miRNAs (miR-19a-3p, miR-186-5p and let-7f). Results: Patients with high platelet reactivity (HPR, based on arachidonic acid-induced platelet aggregometry) had significantly elevated platelet-EVs (CD62+) and leukocyte-EVs (CD45+) concentration compared to patients with normal platelet reactivity at the day of 1 acute-stroke (p = 0.012, p = 0.002, respectively). Diagnostic values of baseline miRNAs and EVs were evaluated with receiver operating characteristic (ROC) curve analysis. The area under the ROC curve for miR-19a-3p was 0.755 (95% CI, 0.63-0.88) p = 0.004, for let-7f, it was 0.874 (95% CI, 0.76-0.99) p = 0.0001; platelet-EVs was 0.776 (95% CI, 0.65-0.90) p = 0.001, whereas for leukocyte-EVs, it was 0.715 (95% CI, 0.57-0.87) p = 0.008. ROC curve showed that pooling the miR-19a-3p expressions, platelet-EVs, and leukocyte-EVs concentration yielded a higher AUC than the value of each individual biomarker as AUC was 0.893 (95% CI, 0.79-0.99). Patients with moderate stroke had significantly elevated miR-19a-3p expression levels compared to patients with minor stroke at the first day of IS. (AUC: 0.867, (95% CI, 0.74-0.10) p = 0.001). Conclusion: Combining different biomarkers of processes underlying IS pathophysiology might be beneficial for early diagnosis of ischemic events. Thus, we believe that in the future circulating biomarkers might be used in the prehospital phase of IS. In particular, circulating plasma EVs and non-coding RNAs including miRNAs are interesting candidates as bearers of circulating biomarkers due to their high stability in the blood and making them highly relevant biomarkers for IS diagnostics

Fast Track Algorithm: How To Differentiate A “Scleroderma Pattern” From A “Non-Scleroderma Pattern”

Objectives: This study was designed to propose a simple “Fast Track algorithm” for capillaroscopists of any level of experience to differentiate “scleroderma patterns” from “non-scleroderma patterns” on capillaroscopy and to assess its inter-rater reliability. Methods: Based on existing definitions to categorise capillaroscopic images as “scleroderma patterns” and taking into account the real life variability of capillaroscopic images described standardly according to the European League Against Rheumatism (EULAR) Study Group on Microcirculation in Rheumatic Diseases, a fast track decision tree, the “Fast Track algorithm” was created by the principal expert (VS) to facilitate swift categorisation of an image as “non-scleroderma pattern (category 1)” or “scleroderma pattern (category 2)”. Mean inter-rater reliability between all raters (experts/attendees) of the 8th EULAR course on capillaroscopy in Rheumatic Diseases (Genoa, 2018) and, as external validation, of the 8th European Scleroderma Trials and Research group (EUSTAR) course on systemic sclerosis (SSc) (Nijmegen, 2019) versus the principal expert, as well as reliability between the rater pairs themselves was assessed by mean Cohen's and Light's kappa coefficients. Results: Mean Cohen's kappa was 1/0.96 (95% CI 0.95-0.98) for the 6 experts/135 attendees of the 8th EULAR capillaroscopy course and 1/0.94 (95% CI 0.92-0.96) for the 3 experts/85 attendees of the 8th EUSTAR SSc course. Light's kappa was 1/0.92 at the 8th EULAR capillaroscopy course, and 1/0.87 at the 8th EUSTAR SSc course. C Conclusion: For the first time, a clinical expert based fast track decision algorithm has been developed to differentiate a “non-scleroderma” from a “scleroderma pattern” on capillaroscopic images, demonstrating excellent reliability when applied by capillaroscopists with varying levels of expertise versus the principal expert and corroborated with external validation.Wo