A comparative study for fiberoptic and video endoscopic determination of the extent in minimal changes of gastric mucosa using indigo dye spraying

1990 ◽  
Vol 4 (2) ◽  
pp. 80-82 ◽  
Author(s):  
Salim Demirci ◽  
Akira Gohchi
2018 ◽  
Vol 8 (4) ◽  
pp. 42-47
Author(s):  
Tien Nguyen Huu ◽  
Tram Le Thi Bao ◽  
Ngoc Nguyen Thi Nhu ◽  
Thang Phan Phuoc ◽  
Khan Nguyen Viet

Background: Curcumin is a major ingredient in turmeric (Curcuma longa L., Zingiberaceae), which has important activities such as anti-tumor, anti-inflammatory, antioxidant, anti-ischemia, protection of gastric mucosa etc,. Curcumin can be considered as a biological marker of turmeric and turmeric products. Objectives: Developing an HPLC method for quantification of curcumin in turmeric powder and turmeric - honey ball pills; applying this method for products on the market. Materials and methods: turmeric powder and turmeric - honey ball pills collected in Thua Thien Hue province. After optimization process, the method was validated and applied to evaluate the content of curcumin. Results: The chromatography analysis was performed with: Zorbaz Eclipse XDB-C18 (150 × 4.6 nm; 5 µm); Mobile phase: acetonitril: 2% acetic acid (45:55), Flow rate was kept constant at 1.0 ml/min; Detector PDA (420 nm). The method was validated for the HPLC system compatibility, specificity, linearity range, precision and accuracy; the recovery greater than 98%. Conclusion: The developed HPLC method can determine curcumin in turmeric powder and turmeric - honey ball pills. Key words: Curcumin, turmeric powder, turmeric-honey ball pills, quantitative determination, HPLC


2020 ◽  
Vol 17 (1) ◽  
pp. 87-94
Author(s):  
Ibrahim A. Naguib ◽  
Fatma F. Abdallah ◽  
Aml A. Emam ◽  
Eglal A. Abdelaleem

: Quantitative determination of pyridostigmine bromide in the presence of its two related substances; impurity A and impurity B was considered as a case study to construct the comparison. Introduction: Novel manipulations of the well-known classical least squares multivariate calibration model were explained in detail as a comparative analytical study in this research work. In addition to the application of plain classical least squares model, two preprocessing steps were tried, where prior to modeling with classical least squares, first derivatization and orthogonal projection to latent structures were applied to produce two novel manipulations of the classical least square-based model. Moreover, spectral residual augmented classical least squares model is included in the present comparative study. Methods: 3 factor 4 level design was implemented constructing a training set of 16 mixtures with different concentrations of the studied components. To investigate the predictive ability of the studied models; a test set consisting of 9 mixtures was constructed. Results: The key performance indicator of this comparative study was the root mean square error of prediction for the independent test set mixtures, where it was found 1.367 when classical least squares applied with no preprocessing method, 1.352 when first derivative data was implemented, 0.2100 when orthogonal projection to latent structures preprocessing method was applied and 0.2747 when spectral residual augmented classical least squares was performed. Conclusion: Coupling of classical least squares model with orthogonal projection to latent structures preprocessing method produced significant improvement of the predictive ability of it.


2021 ◽  
pp. e00242
Author(s):  
Raquel Lahoz ◽  
Juan Pelegrín Sánchez ◽  
Silvia Górriz ◽  
Pilar Calmarza

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