A new aspect of in vitro antimicrobial leukocyte- and platelet-rich plasma activity based on flow cytometry assessment

The current literature suggests that the antibacterial effect of leukocyte- and platelet-rich plasma (L-PRP) is directly related to platelet and leukocyte concentrations. The aim of this study was twofold: first, to evaluate the antimicrobial effect of L-PRP against selected bacterial strains in vitro, and second, to correlate this effect with leukocyte and platelet content in the final concentration. Blood was collected from 20 healthy males, and L-PRP, acellular plasma (AP), and autologous thrombin were consecutively prepared. Flow cytometry analysis of the blood, L-PRP, and AP was performed. The L-PRP gel, liquid L-PRP, and thrombin samples were tested in vitro for their antibacterial properties against seven selected bacterial strains using the Kirby–Bauer disk-diffusion method. There was notable antimicrobial activity against selected bacterial strains. No statistically significant correlations between antimicrobial activities and the platelet concentration in L-PRP were observed. Statistically significant positive correlations between selected leukocyte subtypes and antimicrobial activity were noted. A negative correlation was found between elevated monocyte count and antimicrobial activity of L-PRP against one bacterial strain studied. L-PRP possesses antimicrobial activity and can be potentially useful in the fight against certain postoperative infections. The bactericidal effect of L-PRP is caused by leukocytes, and there exists a relationship among selected leukocyte subtypes and L-PRP antimicrobial activity.     

Assessment of toxicity using dehydrogenases activity and mathematical modeling

Dehydrogenase activity is frequently used to assess the general condition of microorganisms in soil and activated sludge. Many studies have investigated the inhibition of dehydrogenase activity by various compounds, including heavy metal ions. However, the time after which the measurements are carried out is often chosen arbitrarily. Thus, it can be difficult to estimate how the toxic effects of compounds vary during the reaction and when the maximum of the effect would be reached. Hence, the aim of this study was to create simple and useful mathematical model describing changes in dehydrogenase activity during exposure to substances that inactivate enzymes. Our model is based on the Lagergrens pseudo-first-order equation, the rate of chemical reactions, enzyme activity, and inactivation and was created to describe short-term changes in dehydrogenase activity. The main assumption of our model is that toxic substances cause irreversible inactivation of enzyme units. The model is able to predict the maximum direct toxic effect (MDTE) and the time to reach this maximum (T_MDTE). In order to validate our model, we present two examples: inactivation of dehydrogenase in microorganisms in soil and activated sludge. The model was applied successfully for cadmium and copper ions. Our results indicate that the predicted MDTE and T_MDTE are more appropriate than EC₅₀ and IC₅₀ for toxicity assessments, except for long exposure times.