Polythiophene-Chitosan Magnetic Nanocomposite as a Highly Efficient Medium for Isolation of Fluoxetine from Aqueous and Biological Samples

Polythiophene/chitosan magnetic nanocomposite as an adsorbent of magnetic solid phase extraction was proposed for the isolation of fluoxetine in aqueous and biological samples prior to fluorescence detection at 246 nm. The synthesized nanoparticles, chitosan and polythiophene magnetic nanocomposite, were characterized by scanning electron microscopy, FT-IR, TGA, and EDAX. The separation of the target analyte from the aqueous solution containing the fluoxetine and polythiophene/chitosan magnetic nanocomposite was simply achieved by applying external magnetic field. The main factors affecting the extraction efficiency including desorption conditions, extraction time, ionic strength, and sample solution pH were optimized. The optimum extraction conditions were obtained as 10 min for extraction time, 25 mg for sorbent amount, 50 mL for initial sample volume, methanol as desorption solvent, 1.5 mL for desorption solvent volume, 3 min for desorption time, and being without salt addition. Under the optimum conditions, good linearity was obtained within the range of 15–1000 μg L−1 for fluoxetine, with correlation coefficients 0.9994. Furthermore, the method was successfully applied to the determination of fluoxetine in urine and human blood plasma samples. Compared with other methods, the current method is characterized with highly easy, fast separation and low detection limits

Effect of Low-Level Laser on IL-17 Level in GCF during Orthodontic Treatment

Considering the role of inflammatory mediators in both orthodontic movements and the development of periodontal diseases and taking into accountthe role of Interleukin 17 as an important inflammatory mediator in orthodontic treatments and the impact of low-level laser therapy (LLLT) as a new and appropriate adjuvant therapy, the aim of the present study was to investigate the effect of LLLT on IL-17 levels in gingival cervicular fluid (GCF) during orthodontic treatment.Materials & Methods:In this clinical trial study, 12 patients in need of orthodontic treatment were selected. In these patients, one side of the mouth was randomly selected for laser irradiation and the other side as a control. Diode LLL irradiation with a wavelength of 810 nm was performed throughout the gingival Cervicular on days 0, 2, 18, and 30 after orthodontic treatment. Sampling was performed on days 0, 2, 18, and 30 by placing paper points in distal, mesial, palatal, and buccal sulcus of the maxillary fifth molar on the both sidesfor 30 seconds. All samples were then transferred to the laboratory and IL-17 level was determined by ELISA reader. Data were analyzed using Paired t-test and One-way ANOVA.Results:Mean IL-17 levels at day zero (p value = 0.62) and day 2 after orthodontic treatment (p value = 0.19) were not significantly different betweenthe control and laser treated sides, howeverthey were significantly lower in the laser-treated group than the control group on days 18 and 30 after orthodontic treatment (p value < 0.001). The mean IL-17 levels decreased in both groups during the treatment period, but this decreasewas significant on day 18.Conclusion:The results of the present study indicate thetherapeutic role of diode LLL in reducing inflammation, and Il-17 levels in both sides of the mouth gradually decreased over time, and thisdecrease was more pronounced in the laser-treated side than in the control sid

Prediction of Gas Chromatography-Mass Spectrometry Retention Times of Pesticide Residues by Chemometrics Methods

A quantitative structure-retention relationships (QSRRs) method is employed to predict the retention time of 300 pesticide residues in animal tissues separated by gas chromatography-mass spectroscopy (GC-MS). Firstly, a six-parameter QSRR model was developed by means of multiple linear regression. The six molecular descriptors that were considered to account for the effect of molecular structure on the retention time are number of nitrogen, Solvation connectivity index-chi 1, Balaban Y index, Moran autocorrelation-lag 2/weighted by atomic Sanderson electronegativity, total absolute charge, and radial distribution function-6.0/unweighted. A 6-7-1 back propagation artificial neural network (ANN) was used to improve the accuracy of the constructed model. The standard error values of ANN model for training, test, and validation sets are 1.559, 1.517, and 1.249, respectively, which are less than those obtained reveals by multiple linear regressions model (2.402, 1.858, and 2.036, resp.). Results obtained the reliability and good predictability of nonlinear QSRR model to predict the retention time of pesticides

Rapid monitoring of carvacrol in plants and herbal medicines using matrix solid-phase dispersion and gas chromatography flame ionisation detector

<div><p>Matrix solid-phase dispersion (MSPD) method coupled with gas chromatography flame ionisation detector as a quick and easy extraction technique has been developed to extract carvacrol from plants and herbal medicines. Influence of important parameters on the MSPD method efficiency, such as the sorbent material, the ratio of sample to sorbent material, elution solvent and volume of the elution solvent has been evaluated and optimised. Carvacrol was successfully extracted by diatomaceous earth as sorbent with 350 μL of dichloromethane as elution solvent. The calibration curve showed good linearity (<i>r</i>² = 0.9965) and precision (RSD < 8.16%) in the concentration range of 0.5–100 μg mL^− 1 for carvacrol. The limit of detection and limit of quantification were 0.1 and 0.5 μg mL^− 1, respectively. The recoveries were in the range of 74.4–80.5% with relative standard deviation (RSD) values ranging from 8.4% to 9.8%. The reported MSPD extraction method revealed to be simpler and faster than conventional methods used to quantify carvacrol from plants and herbal medicines.</p></div