Energy Dose Parameters Affect Antimicrobial Photodynamic Therapy–Mediated Eradication of Periopathogenic Biofilm and Planktonic Cultures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: This study evaluated the in vitro efficacy of a commercially available aPDT system in eradication of the periopathogens Porphyromonas gingivalis, Fusobacterium nucleatum, and Aggregatibacter actinomycetemcomitans in both planktonic and biofilm cultures. BACKGROUND DATA: Antimicrobial photodynamic therapy (aPDT) is an effective antibacterial approach in vitro; however, few data are available regarding effective light-energy parameters. MATERIALS AND METHODS: Planktonic and biofilm cultures of periopathogens were exposed to a methylene blue-based formulation and irradiated with a 670-nm nonthermal diode laser. Energy doses were varied from 2.3 to 9.4 J/cm(2) through adjustments in illumination time and a constant power density. Controls consisted of no treatment, light only, and photosensitizer only. Temperature changes were recorded in experimental samples before and after illumination. RESULTS: aPDT with an energy dose of 9.4 J/cm(2) was effective in eradicating P. gingivalis, F. nucleatum, and A. actinomycetemcomitans in biofilm and planktonic form. Reductions from control in planktonic cultures at this energy dose were 6.8 +/- 0.7, 5.2 +/- 0.6, and 1.9 +/- 0.6 log(10), respectively, whereas biofilm reductions were 4.5 +/- 1.2, 3.4 +/- 1.1, and 4.9 +/- 1.4 log(10). Decreasing the treatment time produced an energy dose-dependent killing effect in both models. Changes in sample temperature did not exceed 3 degrees C under these exposure parameters. CONCLUSION: This study demonstrated that three important periopathogens are susceptible to aPDT-mediated killing, regardless of whether they are present in planktonic or biofilm form. Furthermore, a clear energy dose-dependence exists with this treatment that should to be taken into account when determining optimal treatment times in clinical application.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it