Examining the antimicrobial and synergistic effect of calcium channel blockers combined with ampicillin and mint essential oil on aerobic gut bacteria
Irma Komljenović (2001)
4th grade student of Secondary school Petrinja, Petrinja (Croatia)
Nikola Mitović, student at the Faculty of medicine, University of Belgrade
Calcium channel blockers (CCBs) are drugs frequently used all around the world as a treatment for high blood pressure, angina pectoris, and atrial dysrhythmia. The role of action implies inhibition of the influx and efflux of calcium through L-type ion channels. Due to the similarity and common origin of ion channels between eukaryotic and prokaryotic cells, we hypothesized that there will be an antimicrobial and synergistic effect of CCBs with other antimicrobial substances (antibiotic – ampicillin, mint essential oil). CCBs of three different chemical classes were used: verapamil (a phenylalkylamine), cortiazem (a benzothiazepine) and nifedipine (a dihydropyridine). Disk diffusion method of the antibiotic susceptibility test was performed to examine the possible antimicrobial effect of verapamil, cortiazem, and nifedipine, in concentrations suitable for intravenous injection in humans, and to test the synergistic effect they have when they are combined with ampicillin or mint essential oil. The tests were performed on isolated strains of Pseudomonas aeruginosa, Streptococcus aureus, Escherichia coli, Enterococcus faecalis, and Bacillus subtilis. The results were analyzed by measuring and comparing the diameter of the inhibition zones in the ImageJ program. The results show that CCBs do not have an antimicrobial effect on the bacterial strains by themselves. Also, there is no synergistic effects of CCBs combined with ampicillin. A synergistic effect of mint essential oil and verapamil was noticed on E. faecalis strains and of mint essential oil and nifedipine on S. aureus strains. Further research should be conducted by performing MIC assays of the combinations that have shown a synergistic effect or by testing the synergistic effect of the CCBs with other antibiotics and essential oils.
Music Genre Classification Using a MFCC-Fed Neural Network
Roman Via-Dufresne Saus (2001)
Universitat Politecnica de Catalunya, Barcelona (Spain)
Barbara Hajdarević, student at the Faculty of Electrical Engineering, University of Belgrade
The aim of this project is to develop a music genre classifying algorithm and to optimize it to obtain the most accurate classifications possible. To do so, MFCC features will be extracted from 30s audio files and fed into a neural network. Different feature extraction methods and artificial neural network architectures are presented and evaluated in this paper. Results show that the best feature extraction methods consist in extracting 13 MFCC using a 20 Hz to 8000 Hz Mel filter bank from full 30 seconds clips and using mean and covariance matrix to feed it into the neural network. It has also been found that the best option for our neural network consists in a simple network with one hidden layer of 10 neurons.