Phenylketonuria (PKU) is an inherited metabolic disorder that requires lifelong adherence to a low-phenylalanine (Phe) diet to prevent severe neurological complications. However, maintaining dietary adherence can be challenging for patients and their families. This systematic review aimed to comprehensively evaluate the factors affecting adherence to a low-Phe diet in patients with PKU. A systematic search of multiple databases was conducted, and 49 studies were included in the final analysis. The quality of evidence was assessed using the Joanna Briggs Institute levels of evidence and the Quality Assessment with Diverse Studies tool. The review identified four main categories of factors influencing dietary adherence: family-related factors (social, psychological, behavioral, and educational), patient-specific factors (psychological, behavioral, educational, and demographic), environmental factors (healthcare professional support, educational and camp-based interventions, and the COVID-19 pandemic), and therapy-related factors (protein substitute formulation, clinic visits, blood tests, and telemedicine). The findings highlight the complex interplay between elements contributing to dietary adherence in PKU patients and underscore the importance of a multifaceted approach to support patients and their families. Future research should prioritize high-quality longitudinal and experimental studies to provide stronger evidence for the PKU community.

The article develops economic and mathematical models as a tool for conducting factor financial analysis of the prospects for the development of an industrial enterprise. The functioning of the developed economic and mathematical models is based on the DuPont model, which allows analyzing the dynamics of the company’s profitability in the course of two-factor and three-factor financial analysis. The proposed model tools are based on the convergence of deterministic financial analysis methods embedded in the DuPont model and simulation methods that allow analysis under the influence of random factors. The constructed economic and mathematical models for forecasting profitability use the company’s retrospective data on its financial condition: the amount of profit, revenue, assets, and equity. The constructed simulation models are implemented in the OMEGA software product and included in the computer technology for predicting the profitability of an industrial enterprise. The architecture of the proposed tools is presented, and the results of simulation experiments performed on models are demonstrated.

A rapid, precise, accurate, and selective high-performance liquid chromatographic method with fluorescence detection has been validated and used for analysis of amisulpride in human plasma after a simple solid-phase extraction procedure. Compounds were separated on a CN column with 0.03 M potassium dihydrogen phosphate (pH 6.5)–acetonitrile 65:35 (v/v) as mobile phase. Fluorescence detection was performed at excitation and emission wavelengths of 274 and 370 nm, respectively. Calibration plots were linear over the concentration range 10–1,000 ng mL−1 in human plasma, and the lower limit of quantification was 10 ng mL−1. Accuracy was between 0.4 and 6.4% and precision was between 3.1 and 7.5%. Amisulpride was sufficiently stable through three freeze–thaw cycles, during storage for 6 h at room temperature, and for 2 months at −22 °C. The method is suitable for the analysis of clinical samples from pharmacokinetic studies.