Search

In this study, spectrophotometry method was combined with artificial intelligence techniques for developing a simple, rapid, low-cost, and accurate approach for the simultaneous determination of Linagliptin (LIN) and Empagliflozin (EMPA) as antidiabetic drugs in mixtures and pharmaceutical formulation. Fuzzy inference system (FIS), adaptive Neuro-fuzzy inference system (ANFIS), and radial basis function neural network (RBF-NN) were proposed to predict the concentration of pharmaceutical components. The mean recovery and root mean square error (RMSE) of FIS were 98.44%, 103.50% and 0.0668, 0.1982 for LIN and EMPA, respectively. The mean recovery percentage of 100.07 and 99.83, as well as RMSE of 0.0033 and 0.0176 were obtained for LIN and EMPA, respectively. On the other hand, MSE related to the RBF-NN was found 1.46 × 10−26 and 1.72 × 10−25 for LIN and EMPA, respectively. Analysis of variance (ANOVA) test did not show a significant difference between high-performance liquid chromatography (HPLC) and proposed methods. The mean recovery (between 91.40% and 98.29%) and relative standard deviation (RSD) (lower than 0.5%) revealed that the suggested methods in a complex matrix such as urine had good predictive ability. Due to the obtained results, these methods can be used in quality control.

In this study, simultaneous measurement of metformin (MET) and linagliptin (LIN) present in synthetic mixtures, antidiabetic tablet, and the biological sample was studied by chemometrics methods along with spectrophotometric technique. These procedures involved feedforward-backpropagation neural network (FFBP-NN) with Levenberg–Marquardt (LM) and comprehensive Grobner bases (CGB) algorithms, as well as least square support vector machine (LS-SVM). The mean square error (MSE) of the LM algorithm was obtained 1.22 × 10−28 (layer=2 with 10 neurons) and 1.93 × 10−27 (layer=3 with 8 neurons) for MET and LIN, respectively. In the CGB algorithm, layer 2 with 10 neurons for both components was introduced as the best layer and neurons with the least error. The optimal parameters of the LS-SVM method, including regularization (γ) and width (σ) parameters with the root mean square error (RMSE) of 0.4416 and 0.1634 were found for MET and LIN, respectively. The proposed methods were implemented on antidiabetic tablet and the results were compared with high-performance liquid chromatography (HPLC) using analysis of variance (ANOVA) test. The urine sample was also studied as a complex matrix by these methods. A combination of spectrophotometry and chemometrics can be used to improve the quality of pharmaceutical products due to its fast and low-cost and no need for the separation step.

The effective removal of dyes from aqueous wastes is among the most important issues for many industrialized countries. Removal of methyl orange (MO) and malachite green (MG) from aqueous solutions were studied using single-walled carbon nanotubes (SWCNTs), carboxylate functionalized single-walled carbon nanotubes (SWCNT-COOH) and amide functionalized single-walled carbon nanotubes (SWCNT-NH2). The adsorption process was found to be controlled by temperature, ionic strength, initial concentration, adsorbent dosage and contact time. The microstructure of carbon nanotubes was characterized using SEM and FTIR. The adsorbents studied exhibits high efficiency for MO and MG adsorption and the equilibrium states could be achieved in 20, 20, 15 (min) for SWCNTs, SWCNT-COOH, SWCNT-NH2, respectively. Adsorption capacity of each adsorbent increased with increasing active groups on the surface of carbon nanotube, where SWCNT-NH2 was the most effectively adsorbent.

INTRODUCTION: The purpose of this study was to compare the subcutaneous tissue responses of freshly mixed or set endodontic root canal sealers (i.e. RoekoSeal, AH26, AH Plus) in Wistar Albino rats. MATERIALS AND METHODS: Seventy-two male albino rats weighing 200-250g were used. The animals were randomly divided into six groups of 12 rats each. Root canal sealers were implanted in subcutaneous tissue in both freshly mixed and set conditions. The animals were sacrificed after 7, 14, and, 60 days. After histological preparation and Hematoxylin and Eosin (H&E) staining, the specimens were evaluated for capsule thickness, severity and extent of inflammation, and necrosis. Results were statistically analyzed using Multivariate ANOVA test. RESULTS: Differences between set and freshly mixed root canal sealers were significant (P=0.014), but not significant between test materials and controls, except for capsule thickness and extent of inflammation between control and AH26 (P=0.019 and P=0.006 respectively). The interaction between the type of material and setting condition was significant for capsule thickness and severity of inflammation in AH26 specimens at 14 and 60 days (P=0.001). CONCLUSION: Based on the results of this study assessing the biocompatibility, both set and freshly mixed states can be used. [Iranian Endodontic Journal 2009;4(4):152-7]