Cranberry Proanthocyanidins Inhibit MMP Production and Activity
Bibliographic record
Abstract
Matrix metalloproteinases (MMPs) produced by resident and inflammatory cells in response to periodontopathogens play a major role in periodontal tissue destruction. Our aim was to investigate the effects of A-type cranberry proanthocyanidins (AC-PACs) on: (i) the production of various MMPs by human monocyte-derived macrophages stimulated with Aggregatibacter actinomycetemcomitans lipopolysaccharide (LPS), and (ii) the catalytic activity of recombinant MMP-1 and MMP-9. The effects of AC-PACs on the expression of 5 protein kinases and the activity of nuclear factor-kappa B (NF-kappaB) p65 in macrophages stimulated with LPS were also monitored. Our results indicated that AC-PACs inhibited the production of MMPs in a concentration-dependent manner. Furthermore, the catalytic activity of MMP-1 and MMP-9 was also inhibited. The inhibition of MMP production was associated with reduced phosphorylation of key intracellular kinases and the inhibition of NF-kappaB p65 activity. AC-PACs thus show potential for the development of novel host-modulating strategies to inhibit MMP-mediated tissue destruction during periodontitis.
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.
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".