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Record W2323977027 · doi:10.1021/jf102120c

Egg-Derived Peptide IRW Inhibits TNF-α-Induced Inflammatory Response and Oxidative Stress in Endothelial Cells

2010· article· en· W2323977027 on OpenAlexafffund
Wuyang Huang, Subhadeep Chakrabarti, Kaustav Majumder, Yanyan Jiang, Sandra T. Davidge

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsWomen and Children’s Health Research InstituteUniversity of Alberta
FundersUniversity of Alberta
KeywordsSuperoxideTumor necrosis factor alphaOxidative stressCell adhesion moleculeMonocyteChemistryInflammationVCAM-1Endothelial stem cellSuperoxide dismutaseAngiotensin IIReactive oxygen speciesBiochemistryBiologyIntracellularCell biologyImmunologyICAM-1EnzymeIn vitroReceptor

Abstract

fetched live from OpenAlex

Oxidative stress and vascular inflammatory response are key mediators of endothelial dysfunction that leads to cardiovascular diseases. A novel peptide, IRW, was previously characterized from egg protein with angiotensin converting enzyme inhibitory activity. The purpose of the study was to investigate the effects and molecular mechanisms of IRW on regulating inflammatory response in endothelial cells. The results showed that tumor necrosis factor-α (TNF-α) significantly increased the protein levels of intercellular adhesion molecule-1 (ICAM-1), vascular cell adhesion molecule-1 (VCAM-1), and monocyte chemotactic protein-1 (MCP-1), whereas pretreatment with IRW inhibited TNF-α-induced increases of ICAM-1, VCAM-1, and MCP-1 production in a concentration-dependent manner. IRW also reduced the levels of superoxide ions in the presence and absence of TNF-α. These results indicate the potential role of IRW in preventing cardiovascular disease as a functional food ingredient or nutraceutical.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.519

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.006
GPT teacher head0.204
Teacher spread0.198 · 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

Citations104
Published2010
Admission routes2
Has abstractyes

Explore more

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