Journal
PHOTODIAGNOSIS AND PHOTODYNAMIC THERAPY
Volume 28, Issue -, Pages 186-191Publisher
ELSEVIER
DOI: 10.1016/j.pdpdt.2019.08.022
Keywords
Bacteria; Fungi; Microbial control; Photoantimicrobial; Photoinactivation; Photodynamic antimicrobial chemotherapy; Antimicrobial Photodynamic Therapy
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Funding
- FAPESP [2013/07937-8, 2016/08593-9, 2016/250952, 2017/22406-0]
- CNPq [465763/20146, 141901/2016-0, 312249/2017-9]
- Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) [16/08593-9] Funding Source: FAPESP
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Background: Antimicrobial Photodynamic therapy (A-PDT) has been used to treat infections. Currently, microbial inactivation data is reported presenting survival fraction averages and standard errors as discrete points instead of a continuous curve of inactivation kinetics. Standardization of this approach would allow clinical protocols to be introduced globally, instead of the piecemeal situation which currently applies. Methods: To this end, we used a power-law function to fit inactivation kinetics and directly report values of lethal doses (LD) and a tolerance factor (T) that informs if inactivation rate varies along the irradiation procedure. A deduced formula was also tested to predict LB for any given survival fraction value. We analyzed the photoantimicrobial effect caused by red light activation of methylene blue (MB-APDT) and by blue light (BL) activation of endogenous microbial pigments against 5 clinically relevant pathogens. Results: Following MB- APDT, Escherichia coli and Staphylococcus aureus cells become increasingly more tolerant to inactivation along the irradiation process (T < 1). Klebsiella pneumoniae presents opposite behavior, i.e., more inactivation is observed towards the end of the process (T > 1). P. aeruginosa and Candida albicans present constant inactivation rate (T(similar to)1). In contrast, all bacterial species presented similar behavior during inactivation caused by BL, i.e., continuously becoming more sensitive to blue light exposure (T > 1). Conclusion: The power-law function successfully fit all experimental data. Our proposed method precisely predicted LD and T values. We expect that these analytical models may contribute to more standardized methods for comparisons of photodynamic inactivation efficiencies.
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