Aims: To assess the success rate and implant stability changes of narrow dental implants (NDIs) during the osseous healing period. Materials and methods: This prospective observational clinical study included 21 patients with narrow alveolar ridge of restricted mesiodistal interdental span who received NDIs. The alveolar ridge width was determined by the ridge mapping technique. Implant stability was measured using Periotest® M immediately after implant insertion then after 4 weeks, 8 weeks and 12 weeks postoperatively. The outcome variables were success rate and implant stability changes during the healing period. The statistical analysis included one-way analysis of variance (ANOVA) and Tukey\'s multiple comparisons test, values < 0.05 w

the current study Included, evaluation the impact of Nitrofurantoin drug on liver in albino mice, 128 male albino mice have been used . Animals treared with (150,200 Mg/Kg) for 8 weeks . NFI caused histological changes in liver represented by , swelling of hepatocytes, disappearance of radial arrangement , vaculation of liver cells , increasing of kupffer cells and appearance of giant cells. NFT caused Congestion of blood vessels and infiltration of inflammatory cells in liver in all used concentrations.

The aim of this study is to provide an overview of various models to study drug diffusion for a sustained period into and within the human body. Emphasized the mathematical compartment models using fractional derivative (Caputo model) approach to investigate the change in sustained drug concentration in different compartments of the human body system through the oral route or the intravenous route. Law of mass action, first-order kinetics, and Fick's perfusion principle were used to develop mathematical compartment models representing sustained drug diffusion throughout the human body. To adequately predict the sustained drug diffusion into various compartments of the human body, consider fractional derivative (Caputo model) to investiga

In this work, mesoporous silica SBA-15 was prepared and functionalized with amine groups (i.e., NH2) to form NH2/SBA-15. The curcumin (CUR) was encapsulated into the surface and pore of NH2/SBA-15 to create CUR@NH2/SBA-15 as an efficient carrier in drug delivery systems (DDSs). The three samples (i.e., SBA-15, NH2/SBA-15, and CUR@NH2/SBA-15) were characterized. The study investigated the effect of the carrier dose, initial CUR concentration, pH, and contact time on the CUR loading efficiency (DLE%) via adsorption. The best DLE% for the SBA-15 and NH2/SBA-15 were found to be 45% and 89.7%, respectively. The Langmuir isotherm had a greater correlation coefficient (R2) of 0.998 for SBA-15. A pseudo-secondorder kinetic model seemed to fit well

Different polymers were prepared by condensation polymerization of sebacic anhydride and adipic anhydride with ethylene glycol and poly(ethylene glycol). Their number average molecular weights were determined by end group analysis. Then, they were grafted on the prepared phthalocyaninatocopper(II) compounds with the general formula (NH2)4PcCu(II) having amino groups of 3,3',3'',3'''- or 4,4',4'',4'''- positions. All prepared polymers, compounds, and phthalocyaninatocopper(II)-grafted polymers were characterized by FTIR. The sizing measurements were carried out in 3,3',3'',3'''- (NH2)4PcCu(II) and 4,4',4'',4'''- (NH2)4PcCu(II) compounds with and without grafting polymers. The results showed that the grafting process led to decreasing in par

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation