A novel metal-organic framework (MOF) sorbent based on tannic acid/copper (TA/Cu) was synthesized and characterized for the application of the anticancer drug imatinib (IMA) from biological samples. The TA/Cu MOF was prepared via a facile coordination reaction and thoroughly characterized by SEM, XRD, and FTIR techniques. Critical parameters influencing the extraction efficiency of imatinib mesylate (IMAM), including pH, ionic strength, desorption solvent, and adsorption-desorption time were optimized. With acetonitrile as the desorption solvent, the method demonstrated a broad linear range of 0.55-300 μg L-1 under ideal conditions. Limits of detection and quantification were found to be 0.16 μg L-1 and 0.55 μg L-1, respectively. For plasma samples spiked at clinically relevant concentrations (5, 20, and 50 μg L-1), the sorbent showed good reusability over four cycles and negligible matrix effects. In comparison to previously published methods, the developed dispersive solid phase extraction method based on TA/Cu MOF performed better in terms of simplicity, enrichment factor, and analytical figures. Another objective of this study was to develop a liquid chromatography with tandem mass spectrometry technique that could be commonly and readily used for therapeutic drug monitoring of imatinib following extraction by solid phase extraction (SPE). Therapeutic monitoring applications can reliably quantify IMA in complex biological matrices as a result of the fast dispersive solid phase extraction (DSPE) procedure and environmentally friendly sorbent. For citation: Russol Abdul Salam Faraj, Noor H.K., Saba H. Jamel, Jasim Jamur M.S. LC-MS/MS method for the determination of imatinib mesylate in blood plasma samples after adsorption by copper tannic acid. ChemChemTech [Izv. Vyssh. Uchebn. Zaved. Khim. Khim. Tekhnol.]. 2025. V. 68. N 3. P. 27-35. DOI: 10.6060/ivkkt.20256803.7121.
The fatty acid composition in the seed and flower of Ligustrun lucidum and olive oil was studied by Gas Chromatography. Results showed that the main components of seed oil were Palmitic (C16:0) 5,893% ,Palmitolic acid (C16:1)0,398%, Steaeic (C18:0)2,911% ,Oleic (C18:1)74,984%,Linoleic (C18:2) 12,959%,and Linolenic (C18:3) 0,997%. The proportion of unsaturated fatty acid was above 89,338%, so the seed oil of L. lucidum ait belonged to unsaturated oil which possessed promising application. The components of flower oil were Palmitic (C16:0) 65,674% ,Palmitolic acid (C16:1)6,516%, Steaeic (C18:0)2,641% ,Oleic (C18:1)14,707%,Linoleic (C18:2) 3,113%,and Linolenic (C18:3) 2,70%. The proportion of unsaturated fatty acid and saturated fatty acid wa
... Show MoreThis study aimed to developing the skills of critical reading for the tenth basic school female students through a training program using the reflective thinking method. The study sample consisted of (64) students. To achieve the objective of the study, the researcher uses the quasi-experiment approach consisting of a control group (32 students) and an experimental group (32 students). The researcher used three research inventories as follows: 1) A list of critical reading skills included (30) skills within three aspects (Recognition – Deduction – Evaluation and Judgment). 2) An executive program using reflective thinking for developing critical reading skills. 3) Achievement test to measure
... Show MoreIn this work the strain energy of tetrahedrane and its nitrogen substituted molecules were calculated by isodesmic reaction method according to DFT quantum chemical fashion, the used basis set was 6-31G/B3-LYP, in addition all structures were optimized by RM1 semi-empirical method. From the obtained data we estimate an empirical equation connect between strain energy of the molecule with charge functions represented by dipole moment of the molecule plus accumulated charge density involved within the tetrahedron frame plus the number of nitrogen atoms. The results indicate the charge spreading factors by polarization and processes are the most important factors in decreasing the strain energy.
Speech is the first invented way of communication that human used age before the invention of writing. In this paper, proposed method for speech analyses to extract features by using multiwavelet Transform (Repeated Row Preprocessing).The proposed system depends on the Euclidian differences of the coefficients of the multiwavelet Transform to determine the beast features of speech recognition. Each sample value in the reference file is computed by taking the average value of four samples for the same data (four speakers for the same phoneme). The result of the input data to every frame value in the reference file using the Euclidian distance to determine the frame with the minimum distance is said to be the "Best Match". Simulatio
... Show MoreThe Aim of this paper is to investigate numerically the simulation of ice melting in one and two dimension using the cell-centered finite volume method. The mathematical model is based on the heat conduction equation associated with a fixed grid, latent heat source approach. The fully implicit time scheme is selected to represent the time discretization. The ice conductivity is chosen
to be the value of the approximated conductivity at the interface between adjacent ice and water control volumes. The predicted temperature distribution, percentage melt fraction, interface location and its velocity is compared with those obtained from the exact analytical solution. A good agreement is obtained when comparing the numerical results of one
In this paper , an efficient new procedure is proposed to modify third –order iterative method obtained by Rostom and Fuad [Saeed. R. K. and Khthr. F.W. New third –order iterative method for solving nonlinear equations. J. Appl. Sci .7(2011): 916-921] , using three steps based on Newton equation , finite difference method and linear interpolation. Analysis of convergence is given to show the efficiency and the performance of the new method for solving nonlinear equations. The efficiency of the new method is demonstrated by numerical examples.
Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B
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