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Response of THP‐1 monocytes to blue light from dental curing lights
Author(s) -
WATAHA J. C.,
LEWIS J. B.,
LOCKWOOD P. E.,
NODA M.,
MESSER R. L.,
HSU S.
Publication year - 2008
Publication title -
journal of oral rehabilitation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.991
H-Index - 93
eISSN - 1365-2842
pISSN - 0305-182X
DOI - 10.1111/j.1365-2842.2007.01806.x
Subject(s) - halogen lamp , materials science , secretion , light intensity , blue light , lipopolysaccharide , medicine , chemistry , optics , optoelectronics , physics
Summary Blue light curing units (wavelengths of 400–500 nm) are a mainstay of restorative dentistry, and several high‐intensity light sources have been developed to polymerize resin composites more rapidly. The biological safety of visible light has been assumed, but some reports of adverse biological effects of blue light in non‐dental contexts support further evaluation of the biological safety of high‐intensity blue light. The current study tested the hypothesis that blue light provokes cell stress responses resulting in the secretion of cytokines or expression of heat‐shock proteins (HSP) in monocytes. Human monocytic cells were irradiated with three light sources (quartz‐tungsten‐halogen, plasma‐arc and laser), then cellular proliferation, secretion of the inflammatory cytokine TNFα and induction of HSP72 were measured. Results indicated that although all three light sources significantly inhibited proliferation of monocytes, the secretion of TNFα was not induced following exposure to blue light and was not potentiated with administration of the activator lipopolysaccharide. Similarly, treatment with the plasma‐arc light, which caused the largest temperature increase in previous studies, did not induce HSP72. The current results do not support activation of monocytes by blue light as an inflammatory risk factor in dental tissues during curing of composites. However, the results of the current study should be further verified in primary monocytes and an animal model before decisions about clinical risks are made.