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Record W4399141017 · doi:10.1021/acs.jafc.4c01594

Food-Derived Up-Regulators and Activators of Angiotensin Converting Enzyme 2: A Review

2024· review· en· W4399141017 on OpenAlexafffund
Z. Wang, Hongbing Fan, Jianping Wu

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2024
Typereview
Languageen
FieldMedicine
TopicRenin-Angiotensin System Studies
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDownregulation and upregulationAngiotensin-converting enzyme 2EnzymeRenin–angiotensin systemPharmacologyReceptorAngiotensin IIChemistryBiologyInternal medicineBiochemistryEndocrinologyMedicineDiseaseCoronavirus disease 2019 (COVID-19)GeneBlood pressure

Abstract

fetched live from OpenAlex

the ACE2/Ang (1-7)/MasR cascade. Given the critical roles of ACE2 in regulating numerous physiological functions, molecules that can upregulate or activate ACE2 show vast therapeutic value. There are only a few ACE2 activators that have been reported, a wide range of molecules, including food-derived compounds, have been reported as ACE2 up-regulators. Effective doses of bioactive peptides range from 10 to 50 mg/kg body weight (BW)/day when orally administered for 1 to 7 weeks. Protein hydrolysates require higher doses at 1000 mg/kg BW/day for 20 days. Phytochemicals and vitamins are effective at doses typically ranging from 10 to 200 mg/kg BW/day for 3 days to 6 months, while Traditional Chinese Medicine requires doses of 1.25 to 12.96 g/kg BW/day for 4 to 8 weeks. ACE2 activation is linked to its hinge-bending region, while upregulation involves various signaling pathways, transcription factors, and epigenetic modulators. Future studies are expected to explore novel roles of ACE2 activators or up-regulators in disease treatments and translate the discovery to bedside applications.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.030
GPT teacher head0.280
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations11
Published2024
Admission routes2
Has abstractyes

Explore more

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