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Record W2610398598 · doi:10.1016/j.jff.2017.04.029

Soy protein-derived ACE-inhibitory peptide LSW (Leu-Ser-Trp) shows anti-inflammatory activity on vascular smooth muscle cells

2017· article· en· W2610398598 on OpenAlex

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.

Bibliographic record

VenueJournal of Functional Foods · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsVascular smooth muscleHydrolysatePeptidePhosphorylationInflammationChemistryBiochemistryCell biologyBiologyEndocrinologySmooth muscleImmunology

Abstract

fetched live from OpenAlex

Soy proteins are a rich source of various bioactive peptides. LSW (Leu-Ser-Trp) was previously identified from thermolysin-digested soy protein hydrolysate as a potent ACE-inhibitory peptide; however, its biological effects on vascular cells have not been elucidated. The present study evaluated anti-oxidant and anti-inflammatory activities of LSW on vascular smooth muscle cells (VSMCs). Ang II promoted oxidative stress and inflammation in VSMCs; adding LSW did not show anti-oxidant activity, while COX-2, but not iNOS, was down-regulated in Ang II-stimulated VSMCs, suggesting its anti-inflammatory activity. AT1R mediates most of the pathological effects of Ang II in VSMCs; LSW down-regulated Ang II-stimulated AT1R expression, via decreased phosphorylation of both Src and ERK1/2. Furthermore, LSW could also reduce the phosphorylation of nuclear transcription factor p50, but not p65. Results of this study suggested a novel function of LSW as an anti-inflammatory agent on VSMCs, which might broaden its uses as functional food ingredients.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.017
GPT teacher head0.242
Teacher spread0.225 · 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