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.

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.

            A spectrophotometric- reverse flow injection analysis (rFIA) method has been proposed for the   determination of Nitrazepam (NIT) in pure and pharmaceutical preparations. The method is based upon the coupling reaction of NIT with a new reagent O-Coumaric acid (OCA) in the presence of sodium periodate in an aqueous solution. The blue color product was measured at 632 nm. The variation (chemical and physical parameters) related with reverse flow system were estimated. The linearity was over the range 15 - 450 µg/mL of NIT with detection limits and limit of quantification of 3.425 and 11.417 µg mL^-1 NIT,respectively. The sample throughput of 28 samples

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.

L-Thyroxine(T4) and triiodothyronine(T3)are iodine-containing hormones produced from thyroglobulin in the thyroid follicular cells. The stimulation of metabolic rate and regulation of growth and development by these hormones appear to be due to their effects on DNA transcription and, thus, protein synthesis. The aqueous extract of vitis vinifera L. was investigated for its effect on hormones in rabbits. The aqueous extract of plant at a dose level of 50µg/rabbit showed highly significant (p<0.05)on levels of hormones T4, TSH but TSH no significant. L-thyroxine sodium treated group showed a highlysignificant increase in T3 and T4 while there was a highly significant decrease in TSH. From the above results, it is concluded for the first time

سرطان البنكرياس هو مرض ذو معدل وفيات مرتفع، ولا يزال التشخيص المبكر لسرطان البنكرياس يمثل تحديًا. يظل معدل البقاء النسبي لمدة 5 سنوات أقل من 8%، والاستراتيجيات العلاجية غير فعالة في زيادة معدلات بقاء المريض على قيد الحياة. في خلايا سرطان البنكرياس، ارتبطت مقاومة العلاج بالتغيرات الجينية التي تؤدي إلى ظهور مسارات خلوية شاذة؛ ولذلك، هناك ما يبرر ايجاد استراتيجيات جديدة لعلاج هذا المرض. هنا، سعينا لاستكشاف

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d