Titanium dioxide nanoparticles (TiO₂ NPs) are generally used in different types of applications such as the industry of plastics, paper industry, paints, toothpaste, cosmetics, sunscreens, and in various lifestyles, because of the vast range of applications and our daily exposure to these nanoparticles and a lack of information on animal and human health this study was designed to reveal dose and time-dependent effects of TiO₂-NPs on the thyroid gland and kidney functions in male rats.

For this study 54, Sprague-Dawley albino adult male rats were classified into three main groups each of 18 rats treated for a particular duration (1,2, and 4) weeks respectively. Each group was subdivided i

Aim: To evaluate the cytotoxic activity of newly synthesized a series of novel HDAC inhibitors comprising sulfonamide as zinc binding group and Isatin derivatives as cap group joined by mono amide linker as required to act as HDAC inhibitors. Materials and Methods: The utilization of sulfonamide as zinc binding group joined by N-alkylation reaction with ethyl-bromo hexanoate as linker group that joined by amide reaction with Isatin derivatives as cap groups which known to possess antitumor activity in the designed of new histone deacetylase inhibitors and using the docking and MTT assay to evaluate the compounds. Results: Four compounds have been synthesized and characterized successfully by ART-FTIR, NMR and ESI-Ms. the compounds w

Five new ceftazidime derivatives were designed and synthesized in an attempt to improve the acid stability and may increase the spectrum of ceftazidime. The synthesized compounds included;  Schiff base of ceftazidime (compound 1), ceftazidime lysine amide Schiff base (compound 2), ceftazidime lysine amide (compound 3), ceftazidime-di-lysine amide Schiff base (compound 4) and ceftazidime-di-lysine amide (compound 5). New ceftazidime derivatives were successfully prepared characterized and identified using spectral and elemental microanalysis (CHNS) analyses and the results comply with the calculated measurements.

Compounds 1 and 2 were subjected to a stability study in phosphate buffer (0.2M, pH 7.4) and in KCl/HCl buffer (0.

New heterocyclic derivatives of quinoline are reported. Reaction of quinoline-2-thiol 4 with hydrazine hydrate gave 2-hydrazionoquinoline 5. Treatment of 5 with CS2 in pyridine afforded 1,2,4-triazolo-[4,3-a]- quinolin-1-2H-thione 6, whereas the reaction of 5 with carboxylic acids namely formic acid or acetic acid, yielded the 1,2,4-triazol-[4,3-a]-quinolin 7 or 5-methyl-1,2,4-triazolo [4,3-a]-quinoline 8 through ring closure. Diazotization of 5 under acidic conditions produced the fused tetrazole compound 9, tetrzolo-[1,5-a]- quinoline. Moreover, treatment of 5 with active methlyene compounds gave two pyrazole derivatives 10 and 11. Azomethines 12a-e were prepared through condensation of 5 with aromatic aldehydes or ketones.

The objective of this experiment was to determine the effects of dietary supplementation with different fat sources on blood parameters of Japanese quail (Coturnix coturnix japonica). Eighty four 7-week old laying quail were randomly assigned to 4 treatment groups (21 birds per group) with 3 replicates for each treatment group and fed for three months on a commercial diet supplemented with 3% of either sunflower oil (T1), flax oil (T2), corn oil (T3) or fish oil (T4). The birds received water and feed ad libitum during the experiment. During the last month of experiment blood samples were collected fortnightly from each bird. The first blood samples collection was used to determine fresh blood parameters, while the second blood samples coll

The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

      In this paper we study and design two feed forward neural networks. The first approach uses radial basis function network and second approach uses wavelet basis function network to approximate the mapping from the input to the output space. The trained networks are then used in an conjugate gradient algorithm to estimate the output. These neural networks are then applied to solve differential equation. Results of applying these algorithms to several examples are presented