Antifungal triazoles affect key non-target metabolic pathways in Solanum lycopersicum L. plants.

Several 1,2,4-triazoles are widely used as systemic fungicides in agriculture because they inhibit fungal 14ɑ-demethylase. However, they can also act on many non-target plant enzymes, thereby affecting phytohormonal balance, free amino acid content, and adaptation to stress. In this study, tomato plants (Solanum lycopersicum L. var. 'Cherrola') were exposed to penconazole, tebuconazole, or their combination, either by foliar spraying or soil drenching, every week, as an ecotoxicological model. All triazole-exposed plants showed a higher content (1.7-8.8 ×) of total free amino acids than the control, especially free glutamine and asparagine were increased most likely in relation to the increase in active cytokinin metabolites 15 days after the first application. Conversely, the Trp content decreased in comparison with control (0.2-0.7 ×), suggesting depletion by auxin biosynthesis. Both triazole application methods slightly affected the antioxidant system (antioxidant enzyme activity, antioxidant capacity, and phenolic content) in tomato leaves. These results indicated that the tomato plants adapted to triazoles over time. Therefore, increasing the abscisic and chlorogenic acid content in triazole-exposed plants may promote resistance to abiotic stress.

Triazoles as a Potential Threat to the Nutritional Quality of Tomato Fruits.

Triazole fungicides can threaten plants as abiotic stressors but can also positively affect plant defense by inducing priming. Thus, plant yield is also both protected and endangered by triazoles that may influence several metabolic pathways during maturation processes, such as the biosynthesis of saccharides or secondary metabolites. Here, Solanum lycopersicum L. plants were exposed to foliar and soil applications of penconazole, tebuconazole, or their combination, and their resulting effect on tomato fruits was followed. The exposure to the equimolar mixture of both triazoles influenced the representation of free proteinogenic amino acids, especially Gln, Glu, Gly, Ile, Lys, Ser and Pro, saccharide content, and led to a significant increase in the contents of total phenolics and flavonoids as well as positive stimulation of the non-enzymatic antioxidant system. Among the identified secondary metabolites, the most abundant was naringenin, followed by chlorogenic acid in tomato peel. In turn, all triazole-treated groups showed a significantly lower content of rosmarinic acid in comparison with the control. Foliar application of penconazole affected the fruit more than other single triazole applications, showing a significant decrease in antioxidant capacity, the total content of secondary metabolites, and the activities of total membrane-bound peroxidases and ascorbate peroxidase.

Using surface plasmon resonance, capillary electrophoresis and diffusion-ordered NMR spectroscopy to study drug release kinetics.

Nanomedicines, including polymer nanocarriers with controlled drug release, are considered next-generation therapeutics with advanced therapeutic properties and reduced side effects. To develop safe and efficient nanomedicines, it is crucial to precisely determine the drug release kinetics. Herein, we present application of analytical methods, i.e., surface plasmon resonance biosensor technology (SPR), capillary electrophoresis, and 1H diffusion-ordered nuclear magnetic resonance spectroscopy, which were innovatively applied for drug release determination. The methods were optimised to quantify the pH-triggered release of three structurally different drugs from a polymer carrier. The suitability of these methods for drug release characterisation was evaluated and compared using several parameters including applicability for diverse samples, the biological relevance of the experimental setup, method complexity, and the analysis outcome. The SPR method was the most universal method for the evaluation of diverse drug molecule release allowing continuous observation in the flow-through setting and requiring a small amount of sample.

Multi-dimensional population balance model development using a breakage mode probability kernel for prediction of multiple granule attributes.

Milling affects not only particle size distributions but also other important granule quality attributes, such as API content and porosity, which can have a significant impact on the quality of the final drug form. The ability to understand and predict the effects of milling conditions on these attributes is crucial. A hybrid population balance model (PBM) was developed to model the Comil, which was validated using experimental results with an R2 of above 0.9. This presented model is dependent on the process conditions, material properties and equipment geometry, such as the classification screen size. In order to incorporate the effects of different quality attributes in the model physics, the dimensionality of the PBM was increased to account for changes in API content and porosity, which also produced predictions for these attributes in the results. Additionally, a breakage mode probability kernel was used to introduce dynamic breakage modes by predicting the probability of attrition and impact mode, which are dependent on the process conditions and feed properties at each timestep.

End-point determination of heterogeneous formulations using inline torque measurements for a high-shear wet granulation process.

In this study, the torque profiles of heterogeneous granulation formulations with varying powder properties in terms of particle size, solubility, deformability, and wettability, were studied, and the feasibility of identifying the end-point of the granulation process for each formulation based on the torque profiles was evaluated. Dynamic median particle size (d50) and porosity were correlated to the torque measurements to understand the relationship between torque and granule properties, and to validate distinction between different granulation stages based on the torque profiles made in previous studies. Generally, the torque curves obtained from the different granulation runs in this experimental design could be categorized into two different types of torque profiles. The primary factor influencing the likelihood of producing each profile was the binder type used in the formulation. A lower viscosity, higher solubility binder resulted in a type 1 profile. Other contributing factors that affected the torque profiles include API type and impeller speed. Material properties such as the deformability and solubility of the blend formulation and the binder were identified as important factors affecting both granule growth and the type of torque profiles observed. By correlating dynamic granule properties with torque values, it was possible to determine the granulation end-point based on a pre-determined target median particle size (d50) range which corresponded to specific markers identified in the torque profiles. In type 1 torque profiles, the end-point markers corresponded to the plateau phase, whereas in type 2 torque profiles the markers were indicated by the inflection point where the slope gradient changes. Additionally, we proposed an alternative method of identification by using the first derivative of the torque values, which facilitates an easier identification of the system approaching the end-point. Overall, this study identified the effects of different variations in formulation parameters on torque profiles and granule properties and implemented an improved method of identification of granulation end-point that is not dependent on the different types of torque profiles observed.