Clinical and Microbiologic Evaluation, by Real-Time Polymerase Chain Reaction, of Non-Surgical Treatment of Aggressive Periodontitis Associated With Amoxicillin and Metronidazole

Background: The aim of the present study is to evaluate the clinical and microbiologic changes resulting from non-surgical periodontal treatment associated with amoxicillin and metronidazole in individuals with aggressive periodontitis. Methods: Fifteen individuals with aggressive periodontitis received non-surgical periodontal treatment and 45 days after completion of treatment were treated with antibiotics. Clinical data and samples of subgingival plaque were collected at baseline, 45 days after the non-surgical periodontal treatment, and 1 month after the use of antimicrobial agents. After 3 and 6 months, only clinical data were collected. The presence and quantification of Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis (Pg), Tannerella forsythia (Tf), Treponema denticola (Td), and Dialister pneumosintes were determined by real-time polymerase chain reaction. Results: All clinical parameters, with the exception of clinical attachment level (CAL), had significantly (P<0.05) improved at the end of the third month after non-surgical therapy associated with antibiotics. There was significant (P<0.05) reduction in the quantities of Td and Tf. After 1 month, there were significant (P<0.05) reductions in the frequencies of Pg and Tf. Conclusion: Non-surgical mechanical treatment associated with the use of amoxicillin and metronidazole led to an improvement in all clinical parameters studied, except for CAL, and significantly reduced the amount of subgingival Tf and Td. J Periodontal 2012;83:744-752.

Programmable logic design of a compact Genetic Algorithm for phasor estimation in real-time

The main objective of this work is to present an efficient method for phasor estimation based on a compact Genetic Algorithm (cGA) implemented in Field Programmable Gate Array (FPGA). To validate the proposed method, an Electrical Power System (EPS) simulated by the Alternative Transients Program (ATP) provides data to be used by the cGA. This data is as close as possible to the actual data provided by the EPS. Real life situations such as islanding, sudden load increase and permanent faults were considered. The implementation aims to take advantage of the inherent parallelism in Genetic Algorithms in a compact and optimized way, making them an attractive option for practical applications in real-time estimations concerning Phasor Measurement Units (PMUs).