The increasing use of antiseptic compounds creates selective pressure cause emergence of antiseptic resistance among Staphylococcus aureus .Resistance mechanism of antiseptic is driven mainly by multi drug resistant (MDR) efflux protein.Sixty five isolates of S.aureuswere collected from different clinical sources and subjected to 11 antibiotics most of them are recognized by efflux systems as extruded substrates. Range of efflux activity was estimated using cartwheel method. Simultaneous discrimination of antiseptic coding genes (qacA/B, smr and norA)as well as nuc and mecA genes among multidrug resistantS.aureus(MRSA) isolates was preformed using multiplex PCR assay

Abstract

The purpose of our study was to develop Dabigatran Etexilate loaded nanostructured lipid carriers (DE-NLCs) using Glyceryl monostearate and Oleic acid as lipid matrix, and to estimate the potential of the developed delivery system to improve oral absorption of low bioavailability drug, different Oleic acid ratios effect on particle size, zeta potential, entrapment efficiency and loading capacity were studied, the optimized DE-NLCs shows a particle size within the nanorange, the zeta potential (ZP) was 33.81±0.73mV with drug entrapment efficiency (EE%) of  92.42±2.31% and a loading capacity (DL%) of 7.69±0.17%. about 92% of drug was released in 24hr in a controlled manner, the ex-vivo intestinal p

Background: Dolutegravir sodium (DTG), used to treat HIV, faces challenges in delivering effective therapeutic concentrations to the brain due to the blood-brain barrier (BBB). Nanostructured lipid carriers (NLCs) combined with in situ gels present a promising strategy for enhancing brain drug delivery via the intranasal route. Objective: To compare brain pharmacokinetics of DTGs delivered via NLC-loaded in situ gel intranasal administration with the conventional intravenous (IV) drug solution. Methods: 80 Wistar rats, which were divided into three groups: two groups consisting of 39 animals each and a control group with 2 animals. Rats were administered with a dose of 1.0 mg/kg of DTGs IV, and DTGs NLC-loaded in situ gel were admin

In this study, NAC-capped CdTe/CdS/ZnS core/double shell QDs were synthesized in an aqueous medium to investigate their utility in distinguishing normal DNA from mutated DNA extracted from biological samples. Following the interaction between the synthesized QDs with DNA extracted from leukemia cases (represents damaged DNA) and that of healthy donors (represents undamaged DNA), differential fluorescent emission maxima and intensities were observed. It was found that damaged DNA from leukemic cells DNA-QDs conjugates at 585 nm while intact DNA (from healthy subjects) DNA–QDs conjugates at 574 nm. The obtained results from the optical analyses indicate that the prepared QDs could be utilized as probe for detecting disrupted DNA th

The permeability estimates for the uncored wells and a porosity function adopting a modified flow zone index-permeability crossplot are given in this work. The issues with implementing that approach were mostly crossplots, due to the influence of geological heterogeneity, did not show a clear connection (scatter data). Carbonate reservoir flow units may now be identified and characterized using a new approach, which has been formally confirmed. Due to the comparable distribution and flow of clastic and carbonate rock fluids, this zoning method is most effective for reservoirs with significant primary and secondary porosity. The equations and correlations here are more generalizable since they connect these variables by combining cor

 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep