MétaCan
Menu
Back to cohort
Record W2093332028 · doi:10.1089/jmf.2011.0265

Anti-Inflammatory and Neuroactive Properties of Selected Fruit Extracts

2012· article· en· W2093332028 on OpenAlex
Kelly C. Heim, Paul Angers, Sébastien Léonhart, Barry W. Ritz

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Medicinal Food · 2012
Typearticle
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsAtrium Innovations (Canada)Champlain Regional CollegeUniversité LavalUniversity of Sudbury
FundersUniversité Laval
KeywordsAntioxidantPharmacologyProlyl endopeptidaseTraditional medicineChemistryFood scienceBiochemistryMedicineEnzymeBiology

Abstract

fetched live from OpenAlex

Epidemiological evidence supports inverse associations between fruit and vegetable intake and incidence of cardiovascular disease and neurodegeneration. Dietary botanicals with salient health benefits include berries and leafy vegetables. Molecular pharmacology research has ascribed these benefits primarily to phenolic constituents and antioxidant activity. The current investigation sought to eluicidate pharmacologic activity of two novel preparations of berry and spinach extracts in vitro. Blueberry and cranberry exhibited the greatest antioxidant activity. In a dose-dependent manner, a proprietary mixture of cranberry and blueberry extracts inhibited inhibitor of κB kinase β, a central node in inflammatory signal transduction. A proprietary mixture of blueberry, strawberry, and spinach extracts inhibited prolyl endopeptidase, a regulator of central neuropeptide stability and an emerging therapeutic target in neurology and psychiatry. These results indicate specific molecular targets of blended dietary plants with potential relevance to inflammation and neurological health.

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.

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)0.000
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 score0.475
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.255
Teacher spread0.227 · 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