Cranberry ( <i>Vaccinium macrocarpon</i> ) extract inhibits matrix metalloproteinase expression in aortic smooth muscle cells by affecting key cell signaling pathways (934.1)
Bibliographic record
Abstract
A whole cranberry ( Vaccinium macrocarpon ) extract was shown to inhibit matrix metalloproteinase (MMP‐2 /MMP‐9) activity (assessed by zymography)in A7R5 aortic smooth muscle cells in vitro . Cranberry extract [CE] decreased cellular viability ~10% post 6 hours of treatment. Treatment of A7R5 cells with 100 ug/mL cranberry extract for 6 hours resulted in increased expression of TIMP‐1 & TIMP‐2 protein levels [inhibitors of MMPs] and decreased protein expression levels of EMMPRIN [an activator of MMPs]. In response to CE treatment, increased expression of JNK‐1, JNK‐2, pJNK‐1, pJNK‐2 & p38 protein levels occurred. No change in ERK‐1, ERK‐2 and pERK‐1 protein levels (assessed by Western blot analyses) occurred in response to cranberry treatment for 6 hours. However, a decrease in p‐p38 and in p‐ERK‐2 protein expression levels was noted in response to CE treatment.Treatment of A7R5 cells with CE (for 6 hours) also resulted in no apparent change in either AKT, pAKT, P‐I‐3 kinase p85 or p110 protein level expression. Treatment of A7R5 cells with CE (100 ug/mL) for 6 hours resulted in inhibition of FAK & p‐FAK protein expression levels . These results suggest that a whole cranberry extract has the ability to inhibit the expression of MMP‐2/‐9 activity in A7R5 aortic smooth muscle cells and suggests that this occurs via alterations in the expression of key protein modulators of MMPs’ expression and also involves changes in signal transduction pathways. (Canadian Institutes of Health Research [CIHR], P.E.I. Health Research Program, The Cranberry Institute ([Wisconsin Board ] funded).
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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) | 0.001 | 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) | 0.001 | 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".