Periprosthetic joint infection (PJI) is a significant complication following total knee arthroplasty (TKA), representing a substantial challenge due to the difficulty in diagnosis and management. The main causes are predominantly common bacteria, but rare pathogens such as can complicate diagnosis and treatment. We report a unique case of a 75-year-old Caucasian patient with a history of multiple comorbidities including obesity, arterial hypertension, total thyroidectomy, rheumatoid arthritis, and prior venous thrombosis.
View Article and Find Full Text PDF: The study explores the potential of various deep eutectic solvents (DESs) to serve as drug delivery systems and pharmaceutical excipients. The research focuses on two primary objectives: evaluating the ability of the selected DES systems to enhance the solubility of two poorly water-soluble model drugs (IBU and MFA), and evaluating their physicochemical properties, including density, viscosity, flow behavior, surface tension, thermal stability, and water dilution effects, to determine their suitability for pharmaceutical applications. : A range of DES systems containing pharmaceutically acceptable constituents was explored, encompassing organic acid-based, sugar- and sugar alcohol-based, and hydrophobic systems, as well as menthol (MNT)-based DES systems with common pharmaceutical excipients.
View Article and Find Full Text PDFThis study focuses on the design, characterization, and optimization of nanostructured lipid carriers (NLCs) loaded with docetaxel for the treatment of skin cancer. Employing a systematic formulation development process guided by Design of Experiments (DoE) principles, key parameters such as particle size, polydispersity index (PDI), zeta potential, and entrapment efficiency were optimized to ensure the stability and drug-loading efficacy of the NLCs. Combined XRD and cryo-TEM analysis were employed for NLC nanostructure evaluation, confirming the formation of well-defined nanostructures.
View Article and Find Full Text PDFThe epidemiology of pandemics is classically viewed using geographical and political borders; however, these artificial divisions can result in a misunderstanding of the current epidemiological state within a given region. To improve upon current methods, we propose a clustering algorithm which is capable of recasting regions into well-mixed clusters such that they have a high level of interconnection while minimizing the external flow of the population towards other clusters. Moreover, we analyze and identify so-called core clusters, clusters that retain their features over time (temporally stable) and independent of the presence or absence of policy measures.
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