ABSTRACT In this study, we reported the evaluation of ruminal parameters and the rate and degree of degradation of biogenic amines (BA) in vitro, using ruminal fluid from sheep fed two different diets (meadow hay and silage of Medicago sativa L.). Herein, the Charolais sheep breed with a ruminal cannula was used to gather samples. Multiple rumen parameters were evaluated after 10 days of the feeding period. Samples were processed using fermenters inoculated by BA (histamine, tyramine, putrescine, cadaverine, spermine, and spermidine) during 8-h fermentation. Levels of BA were determined using ion-exchange chromatography, and volatile fatty acids (VFA) were determined using gas chromatography. More rapid BA degradation was noticed in hay than in haylage. Overall, VFA levels increased with duration of the fermentation, while pH lowered. The rapid increase was observed after 4 h of fermentation. Ammonia concentration had a decreasing trend in silage and increasing in the hay. Hypotheses on BA degradation were accepted. Important knowledge of the development of ruminal parameters in time was obtained, and based on gathered information, it is possible to say that other parameters and their impacts on BA in rumen need to be examined further.

ABSTRACT BACKGROUND: Infections, mostly those associated with colonization of wound by different pathogenic microorganisms, are one of the most serious health complications during a medical treatment. Therefore, this study is focused on the isolation, characterization, and identification of microorganisms prevalent in superficial wounds of patients (n = 50) presenting with bacterial infection. METHODS: After successful cultivation, bacteria were processed and analyzed. Initially the identification of the strains was performed through matrix-assisted laser desorption/ionization time-of-flight mass spectrometry based on comparison of protein profiles (2-30 kDa) with database. Subsequently, bacterial strains from infected wounds were identified by both matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and sequencing of 16S rRNA gene 108. RESULTS: The most prevalent species was Staphylococcus aureus (70%), and out of those 11% turned out to be methicillin-resistant (mecA positive). Identified strains were compared with patients' diagnoses using the method of artificial neuronal network to assess the association between severity of infection and wound microbiome species composition. Artificial neuronal network was subsequently used to predict patients' prognosis (n = 9) with 85% success. CONCLUSIONS: In all of 50 patients tested bacterial infections were identified. Based on the proposed artificial neuronal network we were able to predict the severity of the infection and length of the treatment.