Bacterial Nanocellulose Fortified with Antimicrobial and Anti-Inflammatory Natural Products from Chelidonium majus Plant Cell Cultures.

In this work we developed a bi-functional Bacterial-Nano-Cellulose (BNC) carrier system for cell cultures of Chelidonium majus-a medicinal plant producing antimicrobial compounds. The porous BNC was biosynthesized for 3, 5 or 7 days by the non-pathogenic Komagataeibacter xylinus bacteria and used in three forms: (1) Without removal of K. xylinus cells, (2) partially cleaned up from the remaining K. xylinus cells using water washing and (3) fully purified with NaOH leaving no bacterial cells remains. The suspended C. majus cells were inoculated on the BNC pieces in liquid medium and the functionalized BNC was harvested and subjected to scanning electron microscopy observation and analyzed for the content of C. majus metabolites as well as to antimicrobial assays and tested for potential proinflammatory irritating activity in human neutrophils. The highest content and the most complex composition of pharmacologically active substances was found in 3-day-old, unpurified BNC, which was tested for its bioactivity. The assays based on the IL-1ß, IL-8 and TNF-α secretion in an in vitro model showed an anti-inflammatory effect of this particular biomatrix. Moreover, 3-day-old-BNC displayed antimicrobial and antibiofilm activity against Staphylococcus aureus, Pseudomonas aeruginosa and Candida albicans. The results of the research indicated a possible application of such modified composites, against microbial pathogens, especially in local surface infections, where plant metabolite-enriched BNC may be used as the occlusive dressing.

Recognition of Pharmacological Bi-Heterocyclic Compounds by Using Terahertz Time Domain Spectroscopy and Chemometrics.

In this study, we presented the concept and implementation of a fully functional system for the recognition of bi-heterocyclic compounds. We have conducted research into the application of machine learning methods to correctly recognize compounds based on THz spectra, and we have described the process of selecting optimal parameters for the kernel support vector machine (KSVM) with an additional `unknown' class. The chemical compounds used in the study contain a target molecule, used in pharmacy to combat inflammatory states formed in living organisms. Ready-made medical products with similar properties are commonly referred to as non-steroidal anti-inflammatory drugs (NSAIDs) once authorised on the pharmaceutical market. It was crucial to clearly determine whether the tested sample is a chemical compound known to researchers or is a completely new structure which should be additionally tested using other spectrometric methods. Our approach allows us to achieve 100% accuracy of the classification of the tested chemical compounds in the time of several milliseconds counted for 30 samples of the test set. It fits perfectly into the concept of rapid recognition of bi-heterocyclic compounds without the need to analyse the percentage composition of compound components, assuming that the sample is classified in a known group. The method allows us to minimize testing costs and significant reduction of the time of analysis.

Chemometric Evaluation of THz Spectral Similarity for the Selection of Early Drug Candidates.

In this paper we discuss the link between the domain of physical parameters - molecular descriptors of a drug, and terahertz (THz) spectra. We measured the derivatives of the well-known anti-inflammatory drug Piroxicam using THz spectroscopy and employed Principal Component Analysis to build similarity maps in the molecular descriptor and spectral domains. We observed, that the spatial neighborhood on the molecular descriptors map is highly correlated with the spectral neighbourhood within a group of structurally-similar molecules. We built a Partial Least Squares (PLS) predictive model to quantify the relationship between the spectra and the melting point, which can guide the selection of early drug candidates.

SELECTED ASPECTS OF TERAHERTZ SPECTROSCOPY IN PHARMACEUTICAL SCIENCES.

THz-TDS techniques are applied to investigate selected pharmaceutical samples. Investigations were performed on selected pharmaceutical samples with active pharmaceutical ingredients (API)--famotidine, ranitidine, fenofibrate, lovastatin, simvastatin, aspirin, ketoconazole, acyclovir (hydrated and non-hydrated), on excipients--lactose, glucose (hydrated and non-hydrated), Pluronic 127, and on mixtures of selected compounds. Pseudo-polymorphism effects are considered as well. Examples of the terahertz imaging technique are also given. APIs and excipients can be easily recognized in the terahertz band by their specific "fingerprints" as individual components and in mixtures. The hydration process as a variety of polymorphism can also be easily monitored using the THz technique. Moreover, terahertz light can be useful for the penetration of tablets, giving clear pictures of possible defects in tablet coatings.