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Record W2982474932 · doi:10.3390/md17110613

Antihypertensive and Angiotensin-I-Converting Enzyme (ACE)-Inhibitory Peptides from Fish as Potential Cardioprotective Compounds

2019· review· en· W2982474932 on OpenAlexaff
Soheila Abachi, Laurent Bazinet, Lucie Beaulieu

Bibliographic record

VenueMarine Drugs · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsInhibitory postsynaptic potentialEnzymeAngiotensin-converting enzymeChemistryPharmacologyFish <Actinopterygii>Renin–angiotensin systemACE inhibitorBiochemistryMedicineInternal medicineBiologyFisheryBlood pressure

Abstract

fetched live from OpenAlex

The term metabolic/cardiometabolic/insulin resistance syndrome could generally be defined as the co-occurrence of several risk factors inclusive of systemic arterial hypertension. Not only that organizations, such as the world health organization (WHO) have identified high blood pressure as one of the main risk factors of the cardiometabolic syndrome, but there is also a link between the occurrence of insulin resistance/impaired glucose tolerance and hypertension that would consequently lead to type-2 diabetes (T2D). Hypertension is medicated by various classes of synthetic drugs; however, severe or mild adverse effects have been repeatedly reported. To avoid and reduce these adverse effects, natural alternatives, such as bioactive peptides derived from different sources have drawn the attention of researchers. Among all types of biologically active peptides inclusive of marine-derived ones, this paper's focus would solely be on fish and fishery by-processes' extracted peptides and products. Isolation and fractionation processes of these products alongside their structural, compositional and digestion stability characteristics have likewise been briefly discussed to better address the structure-activity relationship, expanding the reader's knowledge on research and discovery trend of fish antihypertensive biopeptides. Furthermore, drug-likeness of selected biopeptides was predicted by Lipinski's rules to differentiate a drug-like biopeptide from nondrug-like one.

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)0.000
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.255
Teacher spread0.241 · 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

Citations116
Published2019
Admission routes1
Has abstractyes

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