Express Diagnostics of Proteolytic Activity of Periodontopathogens—Methodological Approach

The species spectrum of the oral microbiome is considered to be the key factor in the development and progression of periodontal inflammatory disorders. The “red complex” including Porphyromonas gingivalis, Tannerella forsythia and Treponema denticola has the highest pathogenic potential. These bacteria have several biochemical mechanisms that allow them to colonize and destroy periodontal tissues. Proteolytic enzymes play a crucial role in this process. Early diagnosis of pathological conditions induced by microbial contamination allows for the timely treatment of periodontitis. Otherwise, the development of the disease may lead to tooth loss. A total of 48 patients aged 18 to 65 years old who required professional oral hygiene were recruited for this clinical study. Microbial content analysis of dental plaque from the interdental space and the back of the tongue was performed using real-time PCR. To determine the proteolytic activity of oral bacteria, the new express diagnostic method was applied (diagnostic sensitivity, 0.875; specificity, 0.928). The results demonstrate a strong and significant correlation between the new method and the PCR analysis (r = 0.785, p < 0.001). These results show that the new express method can be valuable as an early diagnostic method for periodontal inflammatory disorders caused by the “red complex” bacteria

Assessment of bitter taste of pharmaceuticals with multisensor system employing 3 way PLS regression

The application of the potentiometric multisensor system (electronic tongue, ET) for quantification of the bitter taste of structurally diverse active pharmaceutical ingredients (API) is reported. The measurements were performed using a set of bitter substances that had been assessed by a professional human sensory panel and the in vivo rat brief access taste aversion (BATA) model to produce bitterness intensity scores for each substance at different concentrations. The set consisted of eight substances, both inorganic and organic - azelastine, caffeine, chlorhexidine, potassium nitrate, naratriptan, paracetamol, quinine, and sumatriptan. With the aim of enhancing the response of the sensors to the studied APIs, measurements were carried out at different pH levels ranging from 2 to 10, thus promoting ionization of the compounds. This experiment yielded a 3 way data array (samples × sensors × pH levels) from which 3wayPLS regression models were constructed with both human panel and rat model reference data. These models revealed that artificial assessment of bitter taste with ET in the chosen set of API's is possible with average relative errors of 16% in terms of human panel bitterness score and 25% in terms of inhibition values from in vivo rat model data. Furthermore, these 3wayPLS models were applied for prediction of the bitterness in blind test samples of a further set of API's. The results of the prediction were compared with the inhibition values obtained from the in vivo rat model