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Record W2028495390 · doi:10.1177/0022034509339487

Cranberry Proanthocyanidins Inhibit MMP Production and Activity

2009· article· en· W2028495390 on OpenAlexafffund
V. D. La, Amy B. Howell, Daniel Grenier

Bibliographic record

VenueJournal of Dental Research · 2009
Typearticle
Languageen
FieldDentistry
TopicOral microbiology and periodontitis research
Canadian institutionsUniversité Laval
FundersCanadian Institutes of Health Research
KeywordsMatrix metalloproteinaseAggregatibacter actinomycetemcomitansChemistryLipopolysaccharideKinaseInflammationCell biologyPhosphorylationIntracellularPeriodontal pathogenMonocyteCancer researchPeriodontitisPorphyromonas gingivalisBiochemistryBiologyImmunologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score0.580

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.075
GPT teacher head0.417
Teacher spread0.342 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations108
Published2009
Admission routes2
Has abstractyes

Explore more

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