Objective
To evaluate the anti-microbial effects of photodynamic therapy (PDT) on infected human teeth ex vivo.
Materials and Methods
Fifty-two freshly extracted teeth with pulpal necrosis and associated periradicular radiolucencies were obtained from 34 subjects. Twenty-six teeth with 49 canals received chemomechanical debridement (CMD) with 6% NaOCl and twenty-six teeth with 52 canals received CMD plus PDT. For PDT, root canal systems were incubated with methylene blue (MB) at concentration of 50 µg/ml for 5 minutes followed by exposure to red light at 665 nm with an energy fluence of 30 J/cm2. The contents of root canals were sampled by flushing the canals at baseline and following CMD alone or CMD+PDT and were serially diluted and cultured on blood agar. Survival fractions were calculated by counting colony-forming units (CFU). Partial characterization of root canal species at baseline and following CMD alone or CMD+PDT was performed using DNA probes to a panel of 39 endodontic species in the checkerboard assay.
Results
The Mantel-Haenszel chi-square test for treatment effects demonstrated the better performance of CMD+PDT over CMD (P=0.026). CMD+PDT significantly reduced the frequency of positive canals relative to CMD alone (P=0.0003). Following CMD+PDT, 45 of 52 canals (86.5%) had no CFU as compared to 24 of 49 canals (49%) treated with CMD (canal flush samples). The CFU reductions were similar when teeth or canals were treated as independent entities. Post-treatment detection levels for all species were markedly lower for canals treated by CMD+PDT than were for those treated by CMD alone. Bacterial species within dentinal tubules were detected in 17/22 (77.3%) and 15/29 (51.7%) of canals in the CMD and CMD+PDT group, respectively (P= 0.034).
Conclusion
Data indicate that PDT significantly reduces residual bacteria within the root canal system, and that PDT, if further enhanced by technical improvements, holds substantial promise as an adjunct to CMD.
Background and Objectives
Photodynamic therapy (PDT) is increasingly being explored for treatment of oral infections. Here, we investigate the effect of PDT on human dental plaque bacteria in vitro using methylene blue (MB)-loaded poly(lactic-co-glycolic) (PLGA) nanoparticles with a positive or negative charge and red light at 665 nm.
Study Design/Materials and Methods
Subgingival plaque samples were obtained from 14 patients with chronic periodontitis. Suspensions of plaque microorganisms from seven patients were sensitized with anionic, cationic PLGA nanoparticles (50 μg/ml equivalent to MB) or free MB (50 μg/ml) for 20 min followed by exposure to red light for 5 min with a power density of 100 mW/cm2. Polymicrobial oral biofilms, which were developed on blood agar in 96-well plates from dental plaque inocula obtained from seven patients, were also exposed to PDT as above. Following the treatment, survival fractions were calculated by counting the number of colony-forming units.
Results
The cationic MB-loaded nanoparticles exhibited greater bacterial phototoxicity in both planktonic and biofilm phase compared to anionic MB-loaded nanoparticles and free MB, but results were not significantly different (p>0.05).
Conclusion
Cationic MB-loaded PLGA nanoparticles have the potential to be used as carriers of MB for PDT systems.
Abstract. This paper describes a large case study that explores the applicability of ontology reasoning to problems in the medical domain. We investigate whether it is possible to use such reasoning to automate common clinical tasks that are currently labor intensive and error prone, and focus our case study on improving cohort selection for clinical trials. An obstacle to automating such clinical tasks is the need to bridge the semantic gulf between raw patient data, such as laboratory tests or specific medications, and the way a clinician interprets this data. Our key insight is that matching patients to clinical trials can be formulated as a problem of semantic retrieval. We describe the technical challenges to building a realistic case study, which include problems related to scalability, the integration of large ontologies, and dealing with noisy, inconsistent data. Our solution is based on the SNOMED CT R ontology, and scales to one year of patient records (approx. 240,000 patients).
It is possible to diagnose accurately complex CHD, including the pulmonary venous connections. When diagnosed prenatally, TAPVC carries a poor prognosis.
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