Potentiometric determination of the local anesthetic procaine in pharmaceutical samples.

In this study, a new potentiometric sensor was developed for the determination of the local anesthetic drug procaine in pharmaceutical samples. Procaine (Pr)-Tetraphenlyborate (TPB) ion-pair was synthesized and used as a sensor material. Potentiometric sensors using the synthesized ion pair (Pr-TPB), poly(vinyl chloride) (PVC) and o-nitrophenyloctyl ether (o-NPOE) in different proportions were prepared and their performance properties were tested.

Advances in Physiologically Based Pharmacokinetic (PBPK) Modeling of Nanomaterials.

Nanoparticles (NPs) have been widely used to improve the pharmacokinetic properties and tissue distribution of small molecules such as targeting to a specific tissue of interest, enhancing their systemic circulation, and enlarging their therapeutic properties. NPs have unique and complicated disposition properties compared to small molecule drugs due to their complex multifunctionality. Physiologically based pharmacokinetic (PBPK) modeling has been a powerful tool in the simulation of the absorption, distribution, metabolism, and elimination (ADME) characteristics of the materials, and it can be used in the characterization and prediction of the systemic disposition, toxicity, efficacy, and target exposure of various types of nanoparticles.

Ceftazidime-avibactam resistance determination in carbapenem-resistant Klebsiella pneumoniae infections before its use in practice.

Introduction: To ensure the appropriate usage of ceftazidime-avibactam (CAZ-AVI), recently introduced in our hospital, we aimed to determine susceptibility rates, enzyme analysis, and clonal relationship among strains, together with clinical data.

Methodology: Between June 1 and September 30, 2021, demographic and microbiological data of the patients were recorded. In the obtained samples, meropenem and colistin minimal inhibitory concentration (MIC) levels, carbapenem resistance genes, and the clonal relationship were studied by molecular methods.

The use of image analysis to study the effect of moisture content on the physical properties of grains.

Designing machines and equipment for post-harvest operations of agricultural products requires information about their physical properties. The aim of the work was to evaluate the possibility of introducing a new approach to predict the moisture content in bean and corn seeds based on measuring their dimensions using image analysis using artificial neural networks (ANN). Experimental tests were carried out at three levels of wet basis moisture content of seeds: 9, 13 and 17%.