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Record W4280545103 · doi:10.1021/acs.jafc.1c07161

Chicken Muscle-Derived ACE2 Upregulating Peptide VVHPKESF Inhibits Angiotensin II-Stimulated Inflammation in Vascular Smooth Muscle Cells <i>via</i> the ACE2/Ang (1–7)/MasR Axis

2022· article· en· W4280545103 on OpenAlexafffund
Hongbing Fan, Wang Liao, Sandra T. Davidge, Jianping Wu

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsWomen and Children’s Health Research InstituteUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaKillam TrustsAlberta Innovates - Technology FuturesEgg Farmers of Canada
KeywordsInflammationDownregulation and upregulationAngiotensin IIVascular smooth muscleReceptorInternal medicineEndocrinologyChemistryPeptideRenin–angiotensin systemAngiotensin-converting enzyme 2MedicineSmooth muscleBiochemistryCoronavirus disease 2019 (COVID-19)

Abstract

fetched live from OpenAlex

This study aimed to evaluate the modulatory effects of four chicken muscle-derived peptides [VRP, LKY, VRY, and VVHPKESF (V–F)] on angiotensin II (Ang II)-induced inflammation in rat vascular smooth muscle A7r5 cells. Only V–F could significantly attenuate Ang II-stimulated inflammation via the inhibition of NF-κB and p38 MAPK signaling, being dependent on the Mas receptor (MasR) not on the Ang II type 1 or type 2 receptor (AT1R or AT2R). V–F accelerated Ang II degradation by enhancing cellular ACE2 activity, which was due to ACE2 upregulation other than a direct ACE2 activation. These findings demonstrated that V–F ameliorated Ang II-induced inflammation in A7r5 cells via the ACE2/Ang (1–7)/MasR axis. Three peptide metabolites of V–F─VHPKESF, PKESF, and SF─were identified but were not considered major contributors to V–F’s bioactivity. The regulation of peptide V–F on vascular inflammation supported its functional food or nutraceutical application in the prevention and treatment of hypertension and cardiovascular diseases.

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 score0.052
Threshold uncertainty score0.657

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 head0.184
Teacher spread0.178 · 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

Citations16
Published2022
Admission routes2
Has abstractyes

Explore more

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