Phthalocyanine derivative as an antimicrobial agent against periodontitis-related multispecies biofilms
Bibliographic record
Abstract
The activity of iron tetracarboxyphthalocyanine (FeTcPc) was investigated in the formation of subgingival biofilm by bacterial species associated with periodontal disease. A multispecies biofilm model was developed using the Calgary biofilm device and incubated at 37 °C under anaerobic conditions for 7 days. Starting from day 3, the biofilm was treated with FeTcPc twice daily for one minute over four days, at concentrations ranging from 1,000 to 10,000 μM. Chlorhexidine at 0.12% and the vehicle used to dissolve the test agent, phosphate-buffered saline (PBS), served as positive and negative controls, respectively. After 7 days, the biofilm metabolic activity was measured using 2,3,5-triphenyl tetrazolium chloride (TTC) to differentiate metabolically active cells from inactive ones. Finally, the microbial profile of the treated biofilm was assessed using the DNA-DNA hybridisation method. FeTcPc at 10,000 μM and chlorhexidine treatments reduced the total bacterial counts, without a significant difference from each other. Additionally, FeTcPc at 10,000 μM inhibited the growth of 7 microorganisms when compared with the negative control, highlighting effects on Porphyromonas gingivalis, Tannerella forsythia and Fusobacterium nucleatum vincentii. The study demonstrated that FeTcPc, at a concentration of 10,000 μM, was as effective as chlorhexidine (0.12%) in reducing the total bacterial counts and well-recognised periodontal pathogens levels in the subgingival biofilm, highlighting the potential of FeTcPc as an alternative to conventional periodontal treatments. These findings indicate that FeTcPc has a promising impact on the inhibition of key bacteria involved in periodontal disease, which may open new perspectives for targeted and less aggressive therapies.
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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 | 0.000 | 0.000 |
| 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".