Many approaches have been developed over time to counter the bioavailability limitations of poorly soluble drugs. With advances in nanotechnology in recent decades, this issue has been approached through the formulation of drugs as nanocrystals. Nanocrystals consist of pure drug(s) and a minimum of surface active agent(s) required for stabilization. They are carrier-free submicron colloidal drug delivery systems with a mean particle size typically in the range of 200 - 500 nm. By reducing particle size to nanoscale, the surface area available for dissolution is increased, and thus bioavailability is enhanced. Drug nanocrystals constitute a versatile formulation approach to enhance the pharmacokinetic and pharmacodynamic properties of poorly soluble drugs. This enhancement is achieved by increasing the dissolution velocity, saturation solubility and mucoadhesion. However, stabilization of nanocrystals remains a major challenge in the development of nanocrystals. Main stability issues include increase in particle size, agglomeration, crystal transformation, and chemical instabilities. as such, combination of steric and ionic stabilizers are required for optimal stabilization. Nanocrystals can be administered by various routes including oral, parenteral, ocular, pulmonary and dermal routes with enhanced pharmacodynamic activity and safety. Functionalization of nanocrystals with radionuclide, imaging moieties and ligands further increases the versatility of nanocrystals. Nanocrystals has been proven successful, as demonstrated by the number of marketed drug products utilizing this technology. The present work provides an overview of the more recent achievements in improving the bioavailability of poorly soluble drugs according to their administration route, and describes the methods developed to overcome physicochemical and stability related problems.
The research aims to employ one of the most important strategies for recovery from the crisis of the Covid-19 pandemic, which ravaged the economies of the entire world and its various sectors, including the banking sector, through financial technology that is based on digital transformation to achieve financial sustainability and the creation of innovative financial value chains in light of the decline in the banking sector as a result of The negative effects of the Covid-19 pandemic, be guided by the relevant international accounting standards to control the risks associated with financial technology. To recover from the Covid-19 crisis, the research came out with a set of recommendations, most notably financial technology from
... Show MoreShumblan (SH) is one of the most undesirable aquatic plants widespread in the irrigation channels and water bodies. This work focuses on boosting the biogas potential of shumblan by co-digesting it with other types of wastes without employing any chemical or thermal pretreatments as done in previous studies. A maximum biogas recovery of 378 ml/g VS was reached using shumblan with cow manure as inoculum in a ratio of 1:1. The methane content of the biogas was 55%. Based on volatile solid (VS) and C/N ratios, biogas productions of 518, 434, and 580 ml/g VS were obtained when the shumblan was co-digested with food wastes (SH:F), paper wastes (SH:P), and green wastes (SH:G) respectively. No significant changes of methane contents were observ
... Show MoreToxic substances have been released into water supplies in recent decades because of fast industrialization and population growth. Fenton electrochemical process has been addressed to treat wastewater which is very popular because of its high efficiency and straightforward design. One of the advanced oxidation processes (AOPs) is electro-Fenton (EF) process, and electrode material significantly affects its performance. Nickel foam was chosen as the source of electro-generated hydrogen peroxide (H2O2) due to its good characteristics. In the present study, the main goals were to explore the effects of operation parameters (FeSO4 concentration, current density, and electrolysis time) on the catalytic perform
... Show MoreA simple and accurate method to determinate furosemide (FUR) based on converting the secondary amine to primary amine with acidic hydrolysis then azotization by nitrous acid and coupled with resorcinol as a coupling agent in aqueous medium at pH 13. The optical characteristic like beers law limit found to be (0.25-2.5) μg.ml−1, detection and quantification limits (0.0196) (0.0654) μg.ml−1respectivly and Sandel sensitivity was 0.006738 μg.cm−2. The least-square method was used to evaluate the regression equation and the correlation coefficient. The resulted azo dye has a maximum absorbance at 430 nm with light oran
AlPO4 catalysts supported with WO3 were prepared by impregnating the catalysts with ammonium metatungstate. The catalysts were checked by X-ray Diffraction (XRD), AFM, and SEM; also, the catalysts analysis was done by X-Ray (EDX). Finally, the N2 adsorption-desorption was used to measure the pore volume and surface area of the catalyst. The prepared catalyst has a surface area of 185.83 m2/g, pore volume of 0.645 cm3/g at a calcination temperature of 500°C for 3 hrs, and particle size of AlPO4 with an average of 35.36 nm. Transesterification of edible oil using WO3/AlPO4 was performed, it was observed that WO3/AlPO4 catalysts give high conversion of edible oil, and this is attributed to the high surface area, smaller particle size, and the
... Show MoreThe rapid increase in the number of older people with Alzheimer's disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage in the brain due to AD leads to changes in the information processing activity of the brain and the EEG which ca
... Show MoreA new 5‐fluorouracil–naproxen conjugate is synthesized as a mutual prodrug for targeting cancer tissues. The structure of the target compound and their intermediate are characterized by their melting point, IR, 1H NMR, 13C NMR, and elemental microanalysis. The cytotoxic activity is preliminarily evaluated using nonsmall lung cancer CRL‐2049, human breast cancer CAL‐51, and one type of normal cell line; rat embryo fibroblast cell line. The synthesized compound shows a good cytotoxic effect at the cancer cell and no significant effect at rat embryo fibroblast cell line.
Toxic substances have been released into water supplies in recent decades because of fast industrialization and population growth. Fenton electrochemical process has been addressed to treat wastewater which is very popular because of its high efficiency and straightforward design. One of the advanced oxidation processes (AOPs) is electro-Fenton (EF) process, and electrode material significantly affects its performance. Nickel foam was chosen as the source of electro-generated hydrogen peroxide (H2O2) due to its good characteristics. In the present study, the main goals were to explore the effects of operation parameters (FeSO4 concentration, current density, and electrolysis time) on the catalytic performance that was optimized by r
... Show MoreThe issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of
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