Influence of bacterial growth modes on the susceptibility to light‐activated disinfection
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
AIM: To evaluate the efficacy of light-activated disinfection (LAD) using methylene blue (MB) and a non-coherent light source on gram-positive and gram-negative bacteria in different growth modes. The influence of different photosensitizer (PS) formulations in the MB-mediated LAD of biofilms was also evaluated. METHODOLOGY: Light-activated disinfection using MB was tested on Enterococcus faecalis in a planktonic suspension, coaggregated suspension and mono-species biofilms and on Pseudomonas aeruginosa in a planktonic suspension and mono-species biofilms. Further, the difference in susceptibility of E. faecalis and P. aeruginosa biofilms to LAD with modified PS formulations was assessed by conventional culturing methods and confocal laser scanning microscopy (CLSM). RESULTS: Higher energy dose was required for LAD of bacteria in a coaggregated suspension and in biofilm compared to their planktonic counterparts. Biofilm mode of growth offered the greatest resistance to LAD in both the tested strains of pathogens (P<0.001). Gram-positive E. faecalis was more susceptible to LAD than the gram-negative P. aeruginosa, and the use of modified PS formulations was found to enhance the efficacy of LAD to destroy the biofilm (P<0.001). CONCLUSIONS: Bacterial growth modes play a vital role in influencing the susceptibility to LAD in a dose-dependent manner. The nature of the PS formulation influences the susceptibility of biofilms to LAD.
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 | 0.003 |
| 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 | 0.001 |
| 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