2022
DOI: 10.1109/tbme.2022.3146567
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Analyzing Efficacy and Safety of Anti-Fungal Blue Light Therapy via Kernel-Based Modeling the Reactive Oxygen Species Induced by Light

Abstract: The goal of this study is to investigate the efficacy, safety, and mechanism of ABL for inactivating Candida albicans (C. albicans), and to determine the best wavelength for treating candida infected disease, by experimental measurements and dynamic modeling. Methods: The changes in reactive oxygen species (ROS) in C. albicans and human host cells under the irradiation of 385, 405, and 415 nm wavelengths light with irradiance of 50 mW/cm 2 were measured. Moreover, a kernel-based nonlinear dynamic model, i.e., … Show more

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Cited by 4 publications
(3 citation statements)
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“…Human cells can be exposed to ROS in one of two ways, either exogenous or endogenous . Exogenous ROS exposure is including but is not limited to UV-light exposure and industrial pollutants.…”
Section: Introductionmentioning
confidence: 99%
“…Human cells can be exposed to ROS in one of two ways, either exogenous or endogenous . Exogenous ROS exposure is including but is not limited to UV-light exposure and industrial pollutants.…”
Section: Introductionmentioning
confidence: 99%
“…Our previous study analyzed the efficacy and safety of Anti-Fungal blue light therapy [50,51], while the effects observed in different cells varied significantly. CCK-8 tests showed a general tendency towards decreased cell viability.…”
Section: Discussionmentioning
confidence: 99%
“…However, although ABL are believed to be caused by the PSs that naturally exist in fungal cells, whose types and amounts are usually unknown, modeling by first-principles becomes even more challenging than modeling PDT. To accommodate these modeling challenges, data-driven modeling methods based on time-series have been investigated [25]- [27]. However, there is still no attempt made to ease the model form and the parameter estimation in the classical MSO models, in a similar data-driven fashion based on measured time-series data.…”
Section: Introductionmentioning
confidence: 99%