Potential of using medicinal plant extracts as photosensitizers for antimicrobial photodynamic therapy.

Antimicrobial photodynamic therapy (APDT) is a promising approach to overcome antimicrobial resistance. However, for widespread implementation of this approach, approved photosensitizers are needed. In this study, we used commercially available preparations (Calendulae officinalis floridis extract, Chamomillae recutitae floridis extract, Achillea millefolii herbae extract; Hypericum perforatum extract; Eucalyptus viminalis folia extract) as photosensitizers for inactivation of gram-negative (Pseudomonas aeruginosa) and gram-positive (Staphylococcus aureus) bacteria. Spectral-luminescent analysis has shown that the major chromophores are of chlorophyll (mainly chlorophyll a and b) and hypericin nature. The extracts are efficient generators of singlet oxygen with quantum yield (Î³Δ ) from 0.40 to 0.64 (reference compound, methylene blue with Î³Δ = 0.52). In APDT assays, bacteria before irradiation were incubated with extracts for 30 min. After irradiation and 24 h of incubation, colony-forming units (CFU) were counted. Upon exposure of P. aeruginosa to radiation of 405 nm, 590 nm, and 660 nm at equal energy dose of 30 J/cm2 (irradiance - 100 mW/cm2 , exposure time - 5 min), the most pronounced effect is observed with blue light (>3 log10 reduction); in case of S. aureus, the effect is approximately equivalent for light of indicated wavelengths and dose (>4 log10 reduction).

Differential diagnosis of follicular tumor by expert systems based on a set of quantitative features of thyrocyte nuclei and aggregates.

OBJECTIVE: To develop expert systems for classification of follicular thyroid tumor at a preoperative stage. STUDY DESIGN: Fine needle aspiration biopsy of the thyroid gland with a histologic conclusion of follicular cancer and follicular adenoma were the object of the morphometric study. General sample size was 4500 nuclei and 3000 aggregates. RESULTS: Quantitative regularities of pathologic changes in thyrocyte nuclei and aggregates in follicular cancer and follicular adenoma were revealed. Threshold values and weighting coefficients of quantitative features of thyrocyte nuclei and aggregates characterizing cancer made the basis of the two expert systems. Expert systems included standard 2-D S-matrix containing threshold values of nuclei and aggregates in cancer and their weighting coefficients as well as 1-D scientific X-matrix designed for filling with quantitative features of the studied object. The diagnosis was verified by the value of a diagnostic index by means of comparing feature values in the corresponding elements of S- and X-matrices. After that, a diagnostic index was calculated taking into account the features' weighting coefficient. CONCLUSION: The developed expert systems based on a set of quantitative features of thyrocyte nuclei and aggregates will allow assessing the malignant potential of a follicular thyroid tumor at a preoperative stage.

Differential diagnosis of follicular cancer and follicular adenoma using an expert system based on a set of qualitative signs of cell atypia.

OBJECTIVE: To determine the efficiency of the developed expert system based on a set of qualitative signs of cell atypia and their weighting coefficients in the differential diagnosis of follicular cancer and follicular adenoma of the thyroid gland. STUDY DESIGN: Sixty cytologic preparations of patients with histologic diagnosis of a follicular cancer and follicular adenoma were investigated. RESULTS: Weighting coefficients for each sign of atypia for both forms of pathology have been calculated with the help of the deduced equation. This allowed creating an expert system by which the function of transforming qualitative signs of cell atypia to a quantitative form was realized. "Strength reserve" according to the diagnostic index value, coincidence of the verified diagnosis with the histologic conclusion, and its invariability for all 12 iterations testified to the reliability of an expert system. Preliminary trials showed the efficiency of an expert system for differentiating the nature of a thyroid follicular tumor to be 97.5%. CONCLUSION: The developed expert system allows high efficiency in making a differential diagnosis of thyroid follicular cancer and follicular adenoma.