A Systematic Evaluation of Curcumin Concentrations and Blue Light Parameters towards Antimicrobial Photodynamic Therapy against Cariogenic Microorganisms
Bibliographic record
Abstract
Dental caries is a highly preventable and costly disease. Unfortunately, the current management strategies are inadequate at reducing the incidence and new minimally invasive strategies are needed. In this study, a systematic evaluation of specific light parameters and aqueous curcumin concentrations for antimicrobial photodynamic therapy (aPDT) was conducted. Aqueous solutions of curcumin were first prepared and evaluated for their light absorbance after applying different ~56 mW/cm2 blue light treatments in a continuous application mode. Next, these same light treatments as well as different application modes were applied to the curcumin solutions and the molar absorptivity coefficient, reactive oxygen species (ROS) release, minimum inhibitory concentration (MIC), and minimum bactericidal concentration (MBC) for Streptococcus mutans and the MIC and minimum fungicidal concentration (MFC) for Candida albicans were measured. After up to 1 min of light treatment, the molar absorptivity of curcumin when added to culture media was lower than that for water only; however, at higher energy levels, this difference was not apparent. There was a noted dependence on both ROS type and cariogenic microorganism species on the sensitivity to both blue light treatment and application mode. In conclusion, this study provides new information towards improving the agonistic potential of aPDT associated with curcumin against cariogenic microorganisms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".