Glibenclamide Mini-tablets with an Enhanced Pharmacokinetic and Pharmacodynamic Performance.

In an attempt to decrease the dose, anticipated side effects, and the cost of production of glibenclamide, GLC, a potent oral hypoglycemic drug, the enhancement of the dissolution and hence the oral bioavailability were investigated. Adsorption and co-adsorption techniques using carriers having a very large surface area and surface active agents were utilized to enhance the drug dissolution. Moreover, the Langmuir adsorption isotherms were constructed to identify the type and mechanism of adsorption. The optimized formulation showing the highest in vitro release was compressed into mini-tablet to facilitate drug administration to elderly patients and those having swallowing difficulties. The produced mini-tablets were tested for their mechanical strength and in vitro release pattern. In addition, the pharmacodynamic and pharmacokinetic studies in New Zealand rabbits were performed using the optimized mini-tablet formulation. Mini-tablets containing GLC co-adsorbate with Pluronic F-68 and Laponite RD showed 100 ± 1.88% of GLC released after 20 min. Pharmacodynamic studies in rabbits revealed significantly higher (p ≤ 0.05) hypoglycemic effect with the optimized mini-tablets at a lower GLC dose compared to mini-tablets containing the commercial GLC dose. Moreover, pharmacokinetic analysis showed significantly higher (p ≤ 0.05) AUC, Cmax, and shorter Tmax. The optimized mini-tablet formulation showed 1.5-fold enhancement of the oral bioavailability compared to mini-tablets containing untreated GLC. It could be concluded that the co-adsorption technique successfully enhanced the oral bioavailability of GLC. Furthermore, the produced mini-tablets have a higher oral bioavailability with a lower GLC dose, which could offer economic benefit for industry as well as acceptability for patients

Crack Width Estimation Using Feed and Cascade Forward Back Propagation Artificial Neural Networks

Automatic crack inspection techniques that limit the necessity of human have the potential to lower the cost and time of the process. In this study, a maximum crack width estimation approach is presented. Seventy nine segments of cracks are used for training the neural networks and twenty six segments are used for examination. The maximum width for each segment is measured using laser scanning microscope and segment image is captured and magnified using the microscope camera in order to obtain the extracted crack profile number of pixels. Feed and cascade forward back propagation artificial neural networks are designed and constructed. The input and output for the networks are the crack width in terms of number of pixels and the maximum estimated crack width respectively. It is shown that, the artificial neural networks technique can effectively be used to estimate the crack width. The feedforward back propagation structure which is designed with two layers and training function TRAINLM gives the best results in examination

Non-coding RNA-directed therapeutics in lung cancer: Delivery technologies and clinical applications

Lung cancer is one of the most aggressive and deadliest health threats. There has been an increasing interest in non-coding RNA (ncRNA) recently, especially in the areas of carcinogenesis and tumour progression. However, ncRNA-directed therapies are still encountering obstacles on their way to the clinic. In the present article, we provide an overview on the potential of targeting ncRNA in the treatment of lung cancer. Then, we discuss the delivery challenges and recent approaches enabling the delivery of ncRNA-directed therapies to the lung cancer cells, where we illuminate some advanced technologies including chemically-modified oligonucleotides, nuclear targeting, and three-dimensional in vitro models. Furthermore, advanced non-viral delivery systems recruiting nanoparticles, biomimetic delivery systems, and extracellular vesicles are also highlighted. Lastly, the challenges limiting the clinical trials on the therapeutic targeting of ncRNAs in lung cancer and future directions to tackle them are explored