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Record W4312127996 · doi:10.3390/molecules27248806

Food Peptides, Gut Microbiota Modulation, and Antihypertensive Effects

2022· review· en· W4312127996 on OpenAlexafffund
Patrick Blondin Tsafack, Chen Li, Apollinaire Tsopmo

Bibliographic record

VenueMolecules · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGut floraDysbiosisChemistryLactobacillusOxidative stressPrebioticBiochemistryPharmacologyBiologyFermentation

Abstract

fetched live from OpenAlex

The gut microbiota is increasingly important in the overall human health and as such, it is a target in the search of novel strategies for the management of metabolic disorders including blood pressure, and cardiovascular diseases. The link between microbiota and hypertension is complex and this review is intended to provide an overview of the mechanism including the production of postbiotics, mitigation of inflammation, and the integration of food biological molecules within this complex system. The focus is on hydrolyzed food proteins and peptides which are less commonly investigated for prebiotic properties. The analysis of available data showed that food peptides are multifunctional and can prevent gut dysbiosis by positively affecting the production of postbiotics or gut metabolites (short-chain fatty acids, polysaccharides, biogenic amines, bile acids). Peptides and the postbiotics then displayed antihypertensive effects via the renin-angiotensin system, the gut barrier, the endothelium, and reduction in inflammation and oxidative stress. Despite the promising antihypertensive effect of the food peptides via the modulation of the gut, there is a lack of human studies as most of the works have been conducted in animal models.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.023
GPT teacher head0.281
Teacher spread0.258 · 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.

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

Citations25
Published2022
Admission routes2
Has abstractyes

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