<p><strong>Objective: </strong>The aim of our study was to compare between flavonoids and phenolic acids contents of leaves and fruits of <em>Melia azedarach</em> since no phytochemical investigation had done previously in Iraq.</p><p><strong>Methods: </strong>The leaves and fruits of <em>Melia azedarach </em>were extracted by soxhlet using 80% ethanol then the dried extract was suspended in water and fractionated using petroleum ether, chloroform, ethyl acetate, and n-butanol. The n-butanol fraction was hydrolyzed by acid and partitioned with ethyl acetate. The different fractions containing flavonoids and phenolic acids were analyzed by HPLC and HPTLC.</p><

Objective: Carbamazepine is typically used for the treatment of seizure disorders and neuropathic pain. One of the major problems with this drug is its low solubility in water; therefore the objective of this study was to enhance the solubility of carbamazepine by complexation with cyclodextrin to be formulated as effervescent and dispersible granules.Methods: Solvent evaporation method was used to prepare, binary (Carbamazepine/β-cyclodextrin) complex and ternary (Carbamazepine/β-cyclodextrin/hydroxypropyl methyl cellulose (HPMC E5). The more soluble complex will be further formulated as unit dose effervescent and dispersible granules. The complexes were evaluated for their solubility, drug content, percentage practical yield and

The aim of present study was to develop solid and liquid  self-microemulsifying drug  delivery system of poorly water soluble drug mebendazole using Aerosil 200 as solid carrier.  Microemulsions are clear, stable, isotropic liquid mixtures of oil, water and surfactant, frequently in combination with a co-surfactant having droplet size range usually in the range of 20-250 nm. Oleic acid, tween 80 and polypropylene glycol were selected as oil, surfactant and co-surfactant respectively and for preparation of stable SMEDDS, micro emulsion region was identified by constructing pseudo ternary phase diagram containing different proportion of surfactant: co-surfactant (1:1, 2:1 and 3:1), oil and water. In brief S/ CoS mix means su

Here, we synthesized three new blended ligand complexes of chromium (III), iron (III), and lanthanum (III) ions with a Schiff base made from the condensation of [o-aminophenol and 2-hydroxyacetophenone in the presence of concentrated sulphoric acid (HL1)] as a primary ligand and o-nitroaniline (L2) as a secondary. The Schiff base and its dual ligand chelate were characterized using several spectroscopic studies, IR, 1HNMR, electronic and mass spectra, in addition to elemental analyses, molar conductivity measurements, and magnetic moments. The spectroscopic and analytical outcomes confirmed the formation of the chelates in a 1:1:1(L1: M: L2) ratio. Similarly, an octahedral structure became counseled for all chelates.

Cilnidipine is a dihydropyridine class of calcium channel blockers, it is classified as a BCS class II drug, characterized by a low oral bioavailability of 13%. Consequently, the utilization of nanoparticle preparation is anticipated to enhance its bioavailability. The objective of the research is to integrate cilnidipine nanoparticles into oral films as a means of enhancing patient adherence. The optimal polymers for producing Cilnidipine films were PVA cold and or HPMC E5 at different concentrations using a casting technique with glycerol as a plasticizer. The Nano suspension-based preparation of Cilnidipine's oral film containing the combination of polymers exhibited a significant enhancement in vitro dissolution, with a percentage excee

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

م.د. فاطمة حميد ،أ.م.د وفاء صباح محمد الخفاجي, International Journal of Psychosocial Rehabilitation,, 2020 - Cited by 1

This study was conducted to determine the Immuno – globulins and complements quantitatively. The result revealed that the concentration of Immunoglobulin M(IgM) was increased significantly in patient group comparing with control group . The concentration of complement protein C4 was increased significantly in patient group comparing with control group.IgG of Candida albicans was detected by using ELISA Technique, the result indicated also that this antibody was found in 628% of the women who infected with Vulvovaginal Candidiasis. The sensitivity and specificity of the test were 63% and 89% respectively.