Silybum marianum, from which silymarin (SM) is extracted, is a medicinal herb. In the Biopharmaceutics Classification System, it is of the class II type, meaning it is almost completely insoluble in water. It has a number of therapeutic properties, including anti-inflammatory as well as properties that promote wound healing.

This research target is to promote the dissolution and solubility of SM by employing a technique called solid dispersion and then incorporating the formula of solid dispersion into a topical gel that can be used for wound healing.

Solid dispersion is a technique used to enhance solubility and dissolve pharmaceuticals that are not water-soluble. This method is widely used because of its low cos

As a well-known oral and intravenous antifungal, voriconazole (VRN) has an extensive history of usage in the medical field. Solid lipid nanoparticles (SLNs) have been produced to treat ocular fungal keratitis in the eye. A 32Box-behnken design was used to produce a variety of new formulas for hot-melt extrusion. The SLNs were evaluated by entrapment efficiency (EE percent), particle size (PS), polydispersity index (PDI), and zeta potential (ZP). A series of in-vitro and in-vivo studies were carried out on the new formula. The produced vesicles’ EE, PS, PDI, and ZP values were all good. SLNs eye drops were numerically adjusted to include carbopol, a stabilizer, lipids, and a surfactant, among other substances. ZP of -36.5 ± 0.20 m

Abstract                                                                                                            

Environmental data (whether pre-emptive or responsive perspect

The rate of gas induction was measured in gas-inducing type mechanically agitated contactors provided with two impellers. A reactor of 0.5 m i.d. was used with a working capacity of 60 liters of liquid. Tap water was used as the liquid phase, and air was used as the gas phase. The bioreactor mixing system consists of two equal diameter stirrers; the top impeller is shrouded-disk/curved-blade turbine with six evacuated bending blades, while the bottom impeller was disk turbine. The impeller speed was varied in the range of 50 to 800 rpm. The ratio of impeller diameter to tank diameter (D/T) and the submergence (S) of upper impeller from the top were varied. The effects of clearance of lower impeller from the tank bottom (C₂) an

Lasmiditan (LAS) was formulated as a nanoemulsion based in situ gel (NEIG)with the aim of improving its oral bioavailability via application intranasally. The solubility of LAS in oils, emulsifiers, and co-emulsifiers was determined to identify nanoemulsion (NE)components. Phase diagrams were constructed to identify the area of nanoemulsification. LAS NE was formulated using the spontaneous nanoemulsification method. Four NEs (F19, F24, F31, and F34) containing 7-15 % oleic acid (OA) as an oily phase, 40-55% labrasol (LR), and transcutol (TC) as emulsifier mixture at (1:1), (2:1), (3:1), and (1:2) ratio with 30-53 % (w/w) aqueous phase, having suitable optical transparency of 95–98%, globule size of 104-140 nm and polydisper

In vivo study revealed that ZnO nanoparticles treatment of Streptococcus SPP contaminated injured skin showed good prognosis and good healing process include complete regeneration of the epithelial cells of the epidermis and increase of cellulartiy of the dermal content compared with untreated group. In conclusion, treatment of S. pyogenes infected skin with Zinc oxide nanoparticles concentration (2 mg/ml) limit the skin damage and localized the lesion to the incision site with good healing process

Background: Conventional  MR imaging is essential for diagnosis and evaluation of the posterior fossa tumors  Objectives: To assess the value of diffusion weighted imaging and apparent diffusion coefficient in making distinction between different histological types of posterior fossa tumors.

Type of the study: Cross-sectional study.

Methods: Brain MRI and DWI assessed 19 patients (12 female and 7 male) with MRI diagnosis of posterior fossa tumors. absolute ADC values of contrast -enhancing solid tumor region and ADC ratio of solid tumor to ADC of normal -appearing deep White matter were compared with histological diagnosis postoperatively .The m

Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles