Inhibition of host- and bacteria-derived proteinases by natural anthocyanins
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Host- and bacteria-derived proteinases are considered to play critical roles in periodontitis progression. This study investigated the ability of a blackcurrant extract and its major anthocyanins (cyanidin-3-O-glucoside, cyanidin-3-O-rutinoside and delphinidin-3-O-rutinoside) to inhibit the activity of matrix metalloproteinases (MMPs), neutrophil elastase and periodontopathogen (Porphyromonas gingivalis, Tannerella forsythia and Treponema denticola) proteinases. MATERIAL AND METHODS: Enzyme inhibition was detected using fluorometric and colorimetric assays after incubating blackcurrant extract and its major anthocyanins (at concentrations of 6.25, 12.5, 25 and 50 μg/mL) with MMPs, elastase or bacterial proteinases, along with their specific substrates. Substrate degradation was recorded every hour for up to 4 h. RESULTS: The blackcurrant extract (50 μg/mL) inhibited all proteinases tested. MMP-1 and MMP-9 were significantly inhibited by pure anthocyanins at concentrations ranging from 6.25 to 50 μg/mL. Elastase activity was inhibited by cyanidin-3-O-glucoside and cyanidin-3-O-rutinoside in the range of 6.25-50 μg/mL and by delphinidin-3-O-rutinoside at 50 μg/mL. P. gingivalis, T. forsythia and T. denticola proteinases were also significantly inhibited by pure anthocyanins. In all cases, enzyme inhibition was time-dependent. CONCLUSION: Our study showed that a blackcurrant extract and its major anthocyanins were able to inhibit the activity of host- and bacteria-derived proteinases. This suggests that such natural compounds may represent promising agents for use in adjunctive treatments for periodontitis.
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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".